Python/ Machine Learning Engineer (Regular/Senior)

🏢 Summary: The role focuses on building and owning reliable data pipelines and MLOps infrastructure for a retail loss prevention project using Spark, Airflow, and Azure. You will develop production-grade Python solutions, automate CI/CD processes, and provision cloud infrastructure as code while enhancing monitoring and observability. The position bridges data science and engineering to deliver robust, scalable ML systems in production. 🗂️ Requirements: Strong experience with Python in production environments, Hands-on experience with PySpark and Spark clusters, Experience with workflow orchestration using Airflow, Experience with Azure or equivalent cloud platforms, Practical experience with Infrastructure as Code, Experience automating CI/CD pipelines with GitHub Actions, Knowledge of data validation and monitoring practices, Experience with Kubernetes in production, Experience with observability and monitoring tools, Upper-intermediate English (B2/C1) 📃 Skills: Python, PySpark, Spark, Airflow, Azure, Terraform, GitHub, CI/CD, Kubernetes, Grafana, Prometheus, MLOps 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction. Project: Loss Prevention Project Scope Loss prevention in retail involves the strategic implementation of processes and technologies designed to identify, mitigate, and prevent the disappearance of inventory. To achieve that an Engineering and a Data Science team within a major UK retailer partner to bridge the gap between experimental ML models and robust, production-grade systems. By embedding engineering excellence into the data science lifecycle, the team ensures that loss prevention insights are delivered with high reliability. In this project you will not only develop high-quality Python code, but also implement trustworthy data pipelines on a big Spark cluster orchestrated with Airflow, setup highly automated CI/CD pipelines with Github Actions, and provision Azure infrastructure as code with Terraform. Tech Stack Python, PySpark, Airflow Azure, IaC (Terraform), CI/CD (Github Actions), Observability (Grafana/Promotheus), MLOps, Kubernetes Challenges Establish a resilient MLOps Ecosystem by integrating robust observability, experiment tracking and automated deployment to model serving infrastructure. Improve the reliability and observability of data pipelines to guarantee trust-worthy data. Advancing DevOps Maturity through the implementation of standardized pipelines, enabling rapid iteration and minimizing manual intervention. Team 3 Engineers What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Proactiveness and a strong sense of ownership, taking full responsibility of project outcomes. Significant experience in Data Engineering, specifically with PySpark, data quality monitoring and workflow orchestration. Proficiency in Azure (or equivalent cloud providers) and hands-on experience with Infrastructure as Code principles. Robust DevOps mindset with practical experience automating CI/CD pipelines via GitHub Actions. A dedicated team player with excellent communication skills who thrives within a cross-functional, collaborative environment. Good command of English (B2/C1 level), comfortable utilizing the language daily. A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: The offer is for an ML Engineer focused on building and maintaining data pipelines and production-grade machine learning solutions in an Azure-based cloud environment. The role involves working with PySpark, Airflow, Kubernetes, and Infrastructure as Code to develop, deploy, and monitor scalable ML systems. You will contribute to forecasting and commodities projects, ensuring reliable data processing, CI/CD automation, and robust observability. 🗂️ Requirements: Strong experience in Python development for production systems, Hands-on experience with PySpark and distributed data processing, Experience with Airflow for workflow orchestration, Proficiency in Azure cloud services, Practical experience with Infrastructure as Code, Experience automating CI/CD pipelines using GitHub Actions, Experience with data quality monitoring and observability, Experience with Kubernetes and Docker, Ability to deploy and monitor ML models in production, Advanced English (B2/C1 level) 📃 Skills: Python, PySpark, Airflow, Spark, Azure, AzureML, Kubernetes, Docker, Terraform, GitHub, GitHubActions, AzureDevOps, pandas, scikit-learn, numpy, Grafana, Prometheus, Git 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be responsible for building and owning data pipelines on a Spark Kubernetes cluster orchestrated with Airflow using PySpark. You will improve and introduce data validation and monitoring to ensure trustworthy data at every stage. Tasks will include provisioning and managing Azure resources using a mature Infrastructure as Code approach, as well as automating everything with GitHub Actions and maintaining CI/CD workflows. You will enhance monitoring to further improve the reliability and stability of deployed ML solutions using the Grafana/Prometheus stack. Additionally, you will collaborate with cross functional teams to ensure the seamless deployment and serving of ML models and actively shape the project’s technical roadmap and direction. Python Expert Cloud (prefered Azure) Advanced IaC Regular GitHub Actions Regular Pyspark Regular Airflow Regular Experience with observability Nice to have MLOps: Proven ability to productionize models and set up monitoring Nice to have Dashboarding / visualization skills Nice to have Kubernetes Nice to have English Advanced Project Forecasting & Commodities Project Scope As an ML Engineer in Forecasting and Commodities, you will be involved in projects that support critical decision making processes, by applying your Python, PySpark, Kubernetes and Cloud (Azure) skills. You will be working in a technically mature ecosystem, implementing new features and covering new use-cases. Part of your responsibilities will be design and implementation of a data science innovation framework, as well making contributions to an overall engineering best practises of the organization. Responsibilities – Developing libraries, tools, and frameworks that standardise and accelerate development and deployment of machine learning models. – Working in an Azure cloud environment, developing model training code in AzureML. Building and maintaining cloud infrastructure with IaC (infrastructure as code). – Working with distributed data processing tools such as Spark, to parallelise computation for Machine Learning. – Diagnosing and resolving technical issues, ensuring availability of high-quality solutions that can be adapted and reused. – Collaborating closely with different engineering and data science teams, providing advice and technical guidance to streamline daily work. – Championing best practices in code quality, security, and scalability by leading by example. – Taking your own, informed decisions moving a business forward. Tech Stack Python, PySpark, Airflow, Docker, Kubernetes, Azure (incl. Azure ML), pandas, scikit-learn, numpy, GitHub Actions, Azure DevOps, Terraform, Git @ GitHub Project Challenges – Building a system that provides accurate and up-to-date business forecasts, by providing a set of tools that can be easily leveraged by data scientists and analysts. – Streamlining the process of onboarding, deployment and patching new ML pipelines. – Collaborating with cross-functional teams enhancing customer experiences through innovative technologies. – Employing DevOps practises for reproducible patterns in multiple business domains. Team 1 engineer from VL, two from client side What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Proactiveness and a strong sense of ownership, taking full responsibility of project outcomes. Significant experience in Data Engineering, specifically with PySpark, data quality monitoring and workflow orchestration. Proficiency in Azure (or equivalent cloud providers) and hands-on experience with Infrastructure as Code principles. Robust DevOps mindset with practical experience automating CI/CD pipelines via GitHub Actions. A dedicated team player with excellent communication skills who thrives within a cross-functional, collaborative environment. Good command of English (B2/C1 level), comfortable utilizing the language daily. A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: The offer is for an ML Engineer role focused on building and maintaining production-ready machine learning pipelines in an Azure-based cloud environment. The position involves deploying models, developing ML frameworks, and supporting forecasting and commodities projects using distributed data processing and DevOps practices. The role combines hands-on engineering with collaboration to standardize and scale AI solutions. 🗂️ Requirements: Strong experience in Python and production-level deployments, Experience with Azure cloud services, Experience with PySpark or other Spark-based distributed processing, Experience with Airflow or similar orchestration tools, Experience with Kubernetes ecosystem, Experience with Docker, Experience with Infrastructure as Code, Experience with CI/CD pipelines, Knowledge of MLOps and model monitoring, Experience with Git version control, Advanced English (B2/C1) 📃 Skills: Python, Azure, AzureML, PySpark, Spark, Airflow, Kubernetes, Docker, Terraform, Git, GitHub, GitHubActions, AzureDevOps, pandas, scikit-learn, numpy, MLOps, CI/CD, IaC 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role Join our team to drive business innovation with production-ready machine learning pipelines. You will play a key role in deploying and maintaining ML workflows, leveraging Azure for cloud computing and on-prem clusters for ETLs. Collaborating closely with Data Scientists, you will contribute to AI-powered projects while shaping the organization’s technical culture. Python Advanced Cloud (prefered Azure) Advanced IaC Regular GitHub Actions Advanced Pyspark Regular Airflow Regular Experience with observability Nice to have MLOps: Proven ability to productionize models and set up monitoring Nice to have Productionize models and set up monitoring Regular Kubernetes Nice to have English Advanced View available projects Project Forecasting and Commodities Project Scope As an ML Engineer in Forecasting and Commodities, you will be involved in projects that support critical decision making processes, by applying your Python, PySpark, Kubernetes and Cloud (Azure) skills. You will be working in a technically mature ecosystem, implementing new features and covering new use-cases. Part of your responsibilities will be design and implementation of a data science innovation framework, as well making contributions to an overall engineering best practises of the organization. Your key responsibilities would be: Developing libraries, tools, and frameworks that standardise and accelerate development and deployment of machine learning models. Working in an Azure cloud environment, developing model training code in AzureML. Building and maintaining cloud infrastructure with IaC (infrastructure as code). Working with distributed data processing tools such as Spark, to parallelise computation for Machine Learning. Diagnosing and resolving technical issues, ensuring availability of high-quality solutions that can be adapted and reused. Collaborating closely with different engineering and data science teams, providing advice and technical guidance to streamline daily work. Championing best practices in code quality, security, and scalability by leading by example. Taking your own, informed decisions moving a business forward. Tech Stack Python, PySpark, Airflow, Docker, Kubernetes, Azure (incl. Azure ML), pandas, scikit-learn, numpy, GitHub Actions, Azure DevOps, Terraform, Git, GitHub. Project Challenges Building a system that provides accurate and up-to-date business forecasts, by providing a set of tools that can be easily leveraged by data scientists and analysts. Streamlining the process of onboarding, deployment and patching new ML pipelines. Collaborating with cross-functional teams enhancing customer experiences through innovative technologies. Employing DevOps practises for reproducible patterns in multiple business domains. Team 3 engineers What we expect in general: Strong experience in writing high-quality Python code and deploying production-level projects. Experience with orchestration tools such as Airflow. Knowledge of Spark or other distributed data processing tools. Experience with Kubernetes ecosystem as a user. Strong experience in Cloud (preferred Azure) and Docker Ability to work in a team and participate in the design process. Strong communicator. Team player with mentoring ability. Proactive and responsible Strategic thinker with big-picture perspective Good command of English (B2/C1). A hybrid model is preferred (2-3 days per week in the Kraków office); alternatively, candidates must be available for on-site collaboration as required (approx. once a month). Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training And a lot more!

🏢 Summary: Machine Learning Engineer role focused on deploying and maintaining production-ready ML pipelines and computer vision solutions on retail edge devices. The position involves building scalable cloud and edge architectures, automating ML workflows, and ensuring reliable deployment across thousands of devices using Azure and Python-based technologies. The role also includes collaboration with Data Scientists and contributing to AI-powered projects through monitoring, optimization, and technical consulting. 🗂️ Requirements: 5+ years of software engineering experience, Bachelor’s or Master’s degree in Computer Science or related field, Expert-level Python skills, Advanced Airflow experience, Advanced Docker experience, Advanced GitHub Actions experience, Strong Azure cloud expertise, Ability to work independently, English proficiency at B2/C1 level, Availability for hybrid work model 📃 Skills: Python, Azure, Docker, Airflow, GitHub, DeepStream, Streamlit, PostgreSQL, Terraform, ETL, CCTV 🏢 Description: VirtusLab is a leading European software consulting and engineering company. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering professionals to make a substantial impact in the software industry. About the role Driving business innovation through production-ready machine learning pipelines. Collaboration focuses on deploying and maintaining ML workflows while leveraging Azure for cloud computing and on-prem clusters for ETLs. The scope of services involves close cooperation with Data Scientists, active contribution to AI-powered projects, and consulting on technical solutions and translating complex details for business stakeholders. Business delivery is achieved through the independent deployment and monitoring of models in production, combined with building and maintaining analytical dashboards for continuous insights. Furthermore, the engagement encompasses driving technical excellence across the project environment by fostering knowledge sharing and delivering high-level technical sessions. Python Expert Cloud (prefered Azure) Advanced Docker Advanced Airflow Advanced GitHub Actions Advanced English Advanced View available projects Project Computer Vision / Integration Project Scope The scope of services for the Machine Learning Engineer involves bridging the gap between data science and operational deployment at scale, focusing on the integration and automation of Machine Learning models directly onto retail edge devices, such as self-checkout tills. The core delivery includes: Development and maintenance of components for processing CCTV data, leveraging technologies like NVidia Deepstream. Streamlining the data onboarding process to enable the creation of specialized solutions by Data Science units. Designing and implementing scalable, high-quality code and architectures within cloud and edge environments. Optimization of data storage and processing in the cloud, selecting the most effective tools and architectures to meet business requirements. Enhancing the monitoring, reliability, and stability of deployed solutions, including the delivery of automated testing suites and simulation environments for edge devices. Fostering technical alignment with cross-functional units to ensure the seamless integration of ML models with retail tills, driving customer experience enhancement through innovative technologies. Tech Stack Python, Docker, DeepStream, Airflow, Azure, GitHub Actions, Streamlit, PostgreSQL, Terraform Project Challenges – Deploying and monitoring deployment to 10,000 devices – Ensuring similar behaviour on all devices at the same time – Dealing with internet interruptions during deployment – Dealing with the raw scale of data from thousands of cameras Project environment 3x Python Engineers, without an SDM, operating mostly in the larger Computer Vision team that, apart from engineers, consists of three Data Scientists, a Data Science Manager and Product Manager. The Engineering Team is distributed in Poland while the broader team is distributed in Poland and the United Kingdom. What we expect in general: Minimum 5 years of general software engineering experience with master’s or bachelor’s degree in Computer Science or related field Expert-level Python programming skills and extensive hands-on experience with Airflow, Docker, and GitHub Actions Strong Azure cloud expertise combined with ownership mindset and proven ability to work independently Good command of English (B2/C1). Availability to work in a hybrid model from time to time. Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training Access to the above perks is optional and completely voluntary for B2B contractors Apply now

🏢 Summary: Opportunity to drive business innovation by building and deploying production-ready machine learning pipelines in a hybrid cloud environment for a major UK retailer. The role focuses on end-to-end ML lifecycle implementation, Azure-based infrastructure provisioning, and developing scalable data pipelines and APIs for price optimisation solutions. You will collaborate closely with data scientists and engineers to productionise models and ensure robust monitoring and DevOps practices. 🗂️ Requirements: Strong experience in Python development, Hands-on experience with full Machine Learning Lifecycle implementation, Experience with Infrastructure as Code for cloud resource provisioning, Experience building data pipelines, preferably with PySpark, Knowledge of production system monitoring, Good English proficiency (B2/C1), Availability for hybrid work model 📃 Skills: Python, PySpark, Airflow, Azure, AzureML, Terraform, Spark, Kubernetes, FastAPI, MLflow, CI/CD, GitHub, Docker, Splunk 🏢 Description: VirtusLab is a leading European software consulting and engineering company. Our mission is to craft clean code and practical solutions with precision and purpose. We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering professionals to make a substantial impact in the software industry. About the role Driving business innovation through production-ready machine learning pipelines. Collaboration focuses on deploying and maintaining ML workflows while leveraging Azure for cloud computing and on-prem clusters for ETLs. The scope of services involves close cooperation with Data Scientists, active contribution to AI-powered projects, and consulting on technical solutions and translating complex details for business stakeholders. Business delivery is achieved through the independent deployment and monitoring of models in production, combined with building and maintaining analytical dashboards for continuous insights. Furthermore, the engagement encompasses driving technical excellence across the project environment by fostering knowledge sharing and delivering high-level technical sessions. Project Scope Delivering price optimisation solutions in close cooperation with a major UK retailer’s data science team. The project aims to enable quick exploration and productionisation of the ML models and respective optimisation algorithms in a hybrid-cloud environment. The ultimate objective is providing APIs for the optimiser to solve pricing class problems across multiple business domains. The scope of cooperation covers: Implementing the end-to-end Machine Learning Lifecycle, starting from data preparation through automated deployment to continuous monitoring of data and models in production. Developing PySpark data pipelines to load and transform large amounts of data to produce significant features used in modelling and analytics. Provisioning all cloud resources supporting model development in AzureML with IaC using Terraform Selecting the best architectural patterns to solve business problems. Building robust and maintainable code in the cloud and on-prem to bring models fast and reliably to production Establishing a mature DevOps culture and developing solutions reusable in multiple business domains. Tech Stack Python (PySpark, Airflow, Azure SDK, fastapi, mlflow), Spark on K8S, Azure ML and IaC with Terraform, CI/CD with GitHub Actions, Docker, Splunk. Challenges Addressing numerous pricing problems in the global retailer world sharing similar structures and constraints. The focus is on building robust solutions reusable across multiple domains, leveraging a hybrid on-prem and cloud infrastructure, and ensuring top quality while maintaining quick iterations. Project Environment The project delivery involves a core engineering team of 5-7 professionals in Poland, collaborating closely with the client’s product management, data science team, and internal engineers. What we expect in general: Strong track record in writing high-quality Python code. Hands-on experience with implementing different stages of the Machine Learning Lifecycle. Experience with Infrastructure as Code to set up Cloud resources. Experience with creating data pipelines (ideally with PySpark). Solid understanding of the importance of monitoring in production systems. Good command of English (B2/C1). Availability to work in a hybrid model from time to time. Seems like lots of expectations, huh? Don’t worry! You don’t have to meet all the requirements. What matters most is your passion and willingness to develop. Apply and find out! A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package Virtusity / in-house training Access to the above perks is optional and completely voluntary for B2B contractors

🏢 Summary: Contract role focused on building and productionising Python-based data and ML systems that support front-office portfolio management and analytics. Involves designing scalable data pipelines, modernising legacy workflows, and delivering reliable solutions integrated with enterprise data platforms. High-impact position working closely with investment teams to enable proprietary models and core analytics. 🗂️ Requirements: Strong professional experience with Python engineering, Experience building ETL or ML-oriented Python workflows, Experience developing robust data pipelines, Experience working with parquet or columnar data formats, Experience with PySpark or distributed data processing, Experience working in Databricks or similar platform environments, Proficiency with Git, Experience with testing and code reviews, Experience with CI/CD pipelines, Understanding of software engineering best practices 📃 Skills: Python, ETL, ML, Parquet, PySpark, Spark, Databricks, Git, CI/CD, Testing, APIs, Containers 🏢 Description: Location: Flexible (Hybrid in Wroclaw) Department: Front‑Office Technology & Analytics Type: Contract About the Role We’re working with a leading global investment organisation that is expanding its front‑office engineering function. This role sits at the intersection of data engineering, applied data science, and front‑office portfolio support , with a focus on building high‑quality Python systems that directly enable portfolio managers, analysts, and risk teams. You’ll work across several investment teams, helping to rewrite key components, productionise POCs, optimise data access patterns, and deliver reliable, scalable pipelines that power core analytics and proprietary models. If you enjoy solving complex data problems, building production systems end‑to‑end, and working closely with front‑office stakeholders, this is a high‑impact opportunity. What You’ll Work On Design, build, and operate Python-based data pipelines (batch & near‑real‑time) reading/writing to governed enterprise storage (e.g., parquet patterns via internal cloud storage). Develop production‑ready ML/data components including feature prep, scoring pipelines, and API‑exposed data services. Support the re‑engineering and migration of legacy workflows into modern Python-based solutions. Partner directly with front‑office portfolio managers and analysts to extend and industrialise proprietary models. Optimise Databricks connectivity and collaborate with platform teams to improve Spark/PySpark workloads. Support portfolio teams with data access, connectivity principles, and technical design for productionisation. Contribute to engineering standards: CI/CD, testing, code reviews, observability, automation, and documentation. Work on POCs through to full production rollout, including rewriting logic from other languages into Python where required. What We’re Looking For Must‑Have Skills Strong, professional-level Python engineering skills (data structures, packaging, typing). Experience with ETL or ML‑oriented Python workflows. Experience building robust data pipelines and working with parquet/columnar formats in governed storage. Exposure to PySpark or distributed data processing . Comfortable working in platform environments (Databricks, containerised services, internal dev platforms). Strong software engineering foundations: Git, testing, code review, CI/CD , documentation.

🏢 Summary: Mid–Senior Python Backend Developer role focused on designing and maintaining scalable backend services, RESTful APIs, and microservices in cloud environments. The position emphasizes Microsoft Azure-based solutions, CI/CD automation, and containerized deployments using Docker and Kubernetes. You will work in an Agile team to deliver secure, high-performance cloud-native applications. 🗂️ Requirements: Commercial experience as Python Backend Developer (mid–senior level), Strong experience with Python, Hands-on experience with Microsoft Azure (App Services, Functions, AKS, Storage), Experience with FastAPI and/or Django, Experience designing RESTful APIs, Experience with microservices architecture, Knowledge of CI/CD pipelines and automated testing, Production experience with Docker and Kubernetes, Knowledge of SQL and NoSQL databases, Understanding of cloud architecture patterns and scalability, Proficiency with Git 📃 Skills: Python, Azure, FastAPI, Django, REST, Microservices, CI/CD, Docker, Kubernetes, SQL, NoSQL, Git, GCP, Databricks, Golang, React, Terraform, Bicep, ARM, Kafka, ServiceBus 🏢 Description: Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics. Tasks: Design, develop, and maintain backend services using Python . Build and optimize RESTful APIs and microservices . Work with Microsoft Azure (priority) to design, deploy, and manage cloud solutions. (Experience with GCP is acceptable as an alternative.) Implement CI/CD pipelines and automated testing workflows. Work with Docker and Kubernetes in production environments. Collaborate in an Agile/Scrum team and participate in code reviews, planning, and architecture discussions. What We're Looking For: Strong commercial experience as a Python Backend Developer (mid–senior level). Hands‑on experience with Azure (App Services, Functions, AKS, Storage, etc.). Experience with FastAPI and/or Django . Proven experience designing RESTful APIs and scalable microservice architectures. Solid understanding of CI/CD , automated testing, and deployment pipelines. Proficiency with Docker and Kubernetes in production. Comfortable working in English and collaborating in cross‑functional teams. Additional Expected Skills: Strong knowledge of SQL/NoSQL databases and data modeling. Understanding of cloud architecture patterns, scalability, and performance optimization. Familiarity with unit, integration, and end‑to‑end testing practices. Proficiency with Git and collaborative development workflows. Awareness of security best practices in cloud and backend environments. What Will Set You Apart: Experience with Databricks or other big‑data/data engineering platforms. Commercial experience with Golang . Full‑stack skills , especially with React. Experience with Infrastructure as Code tools (Terraform, Bicep, ARM templates). Knowledge of event‑driven architectures and messaging systems (Kafka, Azure Service Bus, etc.). Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow. We offer: Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites. “Office as an option” model. You can choose to work remotely or in the office. Workation. Enjoy working from inspiring locations in line with our workation policy. Great Place to Work® certified employer. Flexibility regarding working hours and your preferred form of contract. Comprehensive online onboarding program with a “Buddy” from day 1. Cooperation with top-tier engineers and experts. Unlimited access to the Udemy learning platform from day 1. Certificate training programs. Lingarians earn 500+ technology certificates yearly. Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. Grow as we grow as a company. 76% of our managers are internal promotions. A diverse, inclusive, and values-driven community. Autonomy to choose the way you work. We trust your ideas. Create our community together. Refer your friends to receive bonuses. Activities to support your well-being and health. Plenty of opportunities to donate to charities and support the environment. Modern office equipment. Purchased for you or available to borrow, depending on your location.

🏢 Summary: Founding engineer role in a greenfield, AI-driven initiative to build an intelligent internal platform that enhances developer experience across coding, debugging, testing, and deployment. The position focuses on designing and integrating LLM-powered agents and infrastructure within a large-scale engineering environment. You will collaborate in a globally distributed team to deliver AI tools embedded into everyday developer workflows. 🗂️ Requirements: Strong hands-on experience in Python, Proven experience integrating or building with LLMs, AI agents, or coding assistants, Ability to design and implement API integrations, Experience building distributed or backend systems, Ability to integrate systems with developer tools and services, Proficiency in English for technical collaboration across time zones, Polyglot programming skills and ability to learn new technologies quickly 📃 Skills: Python, TypeScript, Scala, Java, LLMs, OpenAI, Anthropic, APIs, AWS, GRPC, MySQL, GitHub, Slack, Docker, Kubernetes, CI/CD, GCP 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Project scope You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Think of it as an internal startup, with the freedom to innovate and the stability of an established company. Our goal is to design and build an intelligent platform that assists developers at every stage, from coding and debugging to testing and deployment. Your team will be part of a larger 10-person group, with colleagues in California, Amsterdam, and Poland, organised into three focused sub-teams. This role requires collaboration (few meetings a week) with engineers on the US West Coast to ensure our platform meets the needs of our global team. What you will do Design and implement integrations with cutting-edge Large Language Models (LLMs) and APIs (like OpenAI’s models, Anthropic’s Claude, and more). Develop intelligent, agent-based systems to automate and assist in complex software development tasks. Engineer the core infrastructure for our AI agents, including components like MCP servers. Seamlessly weave AI capabilities into the daily workflows of our developers by integrating with essential tools like GitHub, Slack, IDEs, and client internal services, mostly Scala-based. Collaborate within a distributed, international team to research, prototype, and deploy solutions that have a direct impact on developer productivity and satisfaction. Tech stack This is a greenfield project, which means you’ll have a say in the technologies we choose. Nothing is set in stone. However, our environment and the problem space suggest we’ll be working with: Primary Languages: Python, TypeScript, Scala – based on available APIs and existing integration – but actual stack will be determined as the project progresses. The project will be based on internally developed services and solutions, utilising Scala, Java, AWS, GRPC, MySQL and more. What we expect: Proven polyglot programming skills with the ability to rapidly learn new languages, frameworks, and domains Strong, hands-on experience in Python Hands-on, practical experience building with or integrating LLMs, coding assistants, or AI agents. You should be ready to demonstrate your work or discuss your implementation experience during the interview A proactive, self-starter attitude. You take initiative, communicate clearly, and thrive in a collaborative, goal-oriented environment Excellent communication skills in English and the ability to effectively collaborate with team members in the US West Coast time zone Nice to have: A passion for or prior experience in building developer tools, IDE plugins, or enhancing developer workflows Experience with DevOps practices and tools (CI/CD, Docker, Kubernetes, cloud platforms like GCP or AWS) Familiarity with the MLOps or Data Engineering ecosystem, particularly on the integration and tooling side (we are not looking for model researchers or trainers) A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package And a lot more!

🏢 Summary: Join a founding team building an AI-powered internal platform to enhance developer experience across a large-scale engineering organization. The role focuses on designing and integrating LLM-based agents and infrastructure into everyday developer workflows. This greenfield project offers high impact through building intelligent tools that support coding, testing, debugging, and deployment. 🗂️ Requirements: Strong hands-on experience in Python, Practical experience integrating or building with LLMs, AI agents, or coding assistants, Proven polyglot programming ability, Experience designing and implementing API integrations, Ability to collaborate with distributed international teams, Professional proficiency in English 📃 Skills: Python, TypeScript, Scala, Java, AWS, GRPC, MySQL, OpenAI, Anthropic, GitHub, Slack, Docker, Kubernetes, GCP, CI/CD 🏢 Description: We foster a dynamic culture rooted in strong engineering, a sense of ownership, and transparency, empowering our team. As part of the expanding VirtusLab Group, we offer a compelling environment for those seeking to make a substantial impact in the software industry within a forward-thinking organization. About the role You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Project scope You will be a founding member of a new, globally distributed team dedicated to a single mission: revolutionizing internal developer experience in a big technical organization (thousands of developers) via AI-based developer tools. Think of it as an internal startup, with the freedom to innovate and the stability of an established company. Our goal is to design and build an intelligent platform that assists developers at every stage, from coding and debugging to testing and deployment. Your team will be part of a larger 10-person group, with colleagues in California, Amsterdam, and Poland, organised into three focused sub-teams. This role requires collaboration (few meetings a week) with engineers on the US West Coast to ensure our platform meets the needs of our global team. What you will do Design and implement integrations with cutting-edge Large Language Models (LLMs) and APIs (like OpenAI’s models, Anthropic’s Claude, and more). Develop intelligent, agent-based systems to automate and assist in complex software development tasks. Engineer the core infrastructure for our AI agents, including components like MCP servers. Seamlessly weave AI capabilities into the daily workflows of our developers by integrating with essential tools like GitHub, Slack, IDEs, and client internal services, mostly Scala-based. Collaborate within a distributed, international team to research, prototype, and deploy solutions that have a direct impact on developer productivity and satisfaction. Tech stack This is a greenfield project, which means you’ll have a say in the technologies we choose. Nothing is set in stone. However, our environment and the problem space suggest we’ll be working with: Primary Languages: Python, TypeScript, Scala – based on available APIs and existing integration – but actual stack will be determined as the project progresses. The project will be based on internally developed services and solutions, utilising Scala, Java, AWS, GRPC, MySQL and more. What we expect: Proven polyglot programming skills with the ability to rapidly learn new languages, frameworks, and domains Strong, hands-on experience in Python Hands-on, practical experience building with or integrating LLMs, coding assistants, or AI agents. You should be ready to demonstrate your work or discuss your implementation experience during the interview A proactive, self-starter attitude. You take initiative, communicate clearly, and thrive in a collaborative, goal-oriented environment Excellent communication skills in English and the ability to effectively collaborate with team members in the US West Coast time zone Nice to have: A passion for or prior experience in building developer tools, IDE plugins, or enhancing developer workflows Experience with DevOps practices and tools (CI/CD, Docker, Kubernetes, cloud platforms like GCP or AWS) Familiarity with the MLOps or Data Engineering ecosystem, particularly on the integration and tooling side (we are not looking for model researchers or trainers) A few perks of being with us Building tech community Flexible hybrid work model Home office reimbursement Language lessons MyBenefit points Private healthcare Training Package And a lot more!

🏢 Summary: The offer is for a Software Engineer (Data) role focused on building scalable data infrastructure and production-ready ML systems within an AI-driven environment. The position combines backend engineering, data engineering, and MLOps to design high-throughput pipelines and support AI solutions from experimentation to production. The role involves close collaboration with Data Science teams to shape architecture and engineering standards for next-generation data platforms. 🗂️ Requirements: 4+ years of software engineering experience, Strong proficiency in Python, Experience building scalable production systems, Experience with data-intensive applications and SQL databases, Knowledge of data modeling and query optimization, Experience with Terraform, Kubernetes, Docker or similar tools, Understanding of CI/CD pipelines and Infrastructure as Code, Experience implementing automated testing and clean architecture principles, Ability to productionize ML solutions with Data Science teams 📃 Skills: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker, Airflow, SQL, CI/CD, AWS, Snowflake, DBT, MLOps 🏢 Description: Our client helps small teams power big businesses with the must-have platform for intelligent marketing automation. Customers from over 170 countries depend on the Client’s mix of pre-built automation and integration to power personalized marketing, transactional emails, and one-to-one CRM interactions throughout the customer lifecycle. We’re looking for a Software Engineer (Data) to join our client’s growing AI and Data organization and help build the scalable foundations behind next-generation data and ML systems. In this role, you won’t just be working with data infrastructure; you’ll be shaping the software architecture, engineering standards, and production-ready platforms that power the company’s AI ecosystem. This is more than a traditional backend or data engineering position. You’ll work at the intersection of software engineering, data, and AI, partnering closely with Data Science and AI teams to bridge the gap between experimentation and production. From designing resilient systems to building scalable MLOps pipelines, your work will directly influence how AI solutions are developed, deployed, and scaled across the organization. Key takeaways: Stack: Python, MySQL, PostgreSQL, Spark, Terraform, Kubernetes, Docker Salary : 20 000 - 23 000 PLN gross/month, Contract of employment (+10% annual bonus, 75% Creative Tax) Working model: Hybrid, once a week in the office Location: Krakow, ul. Konopnickiej Recruitment process: Call with MOTIFE recruiter (30 min) Interview with Hiring Manager (45 min) Technical interview, live coding (1h) Cross-functional interview (1h) Responsibilities: Design, develop, and maintain scalable high-throughput data pipelines across complex data ecosystems. Build and optimize data models, schemas, and database structures to ensure long-term scalability and performance. Implement engineering best practices, including automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform). Partner closely with AI and Data Science teams to productionize machine learning solutions and develop scalable MLOps pipelines. Engineer and maintain feature stores and data infrastructure supporting AI-driven initiatives. Monitor, maintain, and improve the reliability and efficiency of containerized environments using Kubernetes, Docker, and Airflow. Ensure platform stability, observability, and operational excellence through proactive system monitoring and health checks. Collaborate cross-functionally with engineering and business stakeholders to translate complex technical concepts into actionable insights. Contribute to the architectural direction and scalability of the organization’s AI and data platforms. Drive the adoption of robust software engineering standards across data and infrastructure projects. Requirements: 4+ years of experience in software engineering, with strong hands-on experience in backend development and building scalable production systems. Strong proficiency in Python and solid software engineering fundamentals, including clean architecture, testing, and maintainable code practices. Experience working with data-intensive applications, databases, and SQL, including data modeling and query optimization. Exposure to modern data engineering, cloud, or infrastructure environments, with familiarity in tools such as Terraform, Kubernetes, Docker, or similar technologies. Understanding of CI/CD pipelines, Infrastructure as Code, and general engineering best practices. Interest in AI/ML ecosystems and willingness to work closely with Data Science and AI teams on productionizing ML solutions. Familiarity with cloud platforms and modern data stack technologies such as AWS, Snowflake, Spark, or DBT is considered a strong plus. Ownership mindset and comfort working in evolving, fast-moving environments where systems and processes are still being built. What we offer: Health Benefits 1. Medical Full coverage for employees and their dependents through LUX MED. Employees have access to the “Premium” package, providing enhanced coverage and greater access to care. A client pays 100% of the premium for employees and 50% for dependents. 2. Dental No additional cost for dental coverage- integrated into LUX MED medical plan. 3. Vision Reimbursement for vision expenses up to 400 PLN every 2 years. Mental Health Tools Access to TELUS Health EAP to provide support and resources in a time of need. Additional Benefits 10% annual bonus 75% Creative Tax Vacation: 26 days. Home Office Stipend: One-time $150 equivalent home office stipend to outfit their home office. Calm Subscription: Premium subscription access to Calm, the #1 app for sleep, meditation, and relaxation. Hub Perks: Receive meal and transportation benefits when traveling to the Poland Hub. Baby Swag: If you have a baby or adopt, you’ll receive a company-branded first bath bundle. Sabbatical Program: After 5 years of employment, receive a month-long paid sabbatical leave, with a sabbatical leave bonus.