Python Software Engineer with LLM (Principal)

🏢 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: Opportunity to join a newly formed, globally distributed team building an AI-powered internal developer platform for a large-scale engineering organization. The role focuses on designing and integrating LLM-based tools and agent systems that enhance coding, testing, and deployment workflows. You will help architect and implement core AI infrastructure and integrations within a greenfield, startup-like environment. 🗂️ Requirements: Hands-on experience integrating or building with LLMs, AI agents, or coding assistants, Strong experience in Scala or another modern JVM language (Kotlin or Java 17+), Proven polyglot programming ability, Experience designing and implementing API integrations, Ability to collaborate in a distributed team across time zones, Professional English communication skills 📃 Skills: Python, TypeScript, Scala, Java, Kotlin, LLM, OpenAI, Anthropic, API, AWS, GRPC, MySQL, 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. 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. Strong, hands-on experience in at least one of the following: Scala, or another modern JVM language (e.g., Kotlin, Java 17+). 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: Founding engineer role in a greenfield, AI-driven internal platform aimed at revolutionizing developer experience at scale through LLM-powered tools and agent-based systems. The position focuses on designing and integrating AI capabilities into daily development workflows across a large, globally distributed organization. You will collaborate internationally to build core infrastructure and intelligent automation supporting coding, testing, and deployment processes. 🗂️ Requirements: Hands-on experience building or integrating LLMs, AI agents, or coding assistants, Strong experience in Scala or another modern JVM language, Proven polyglot programming ability, Experience designing and implementing API integrations, Ability to build and maintain backend infrastructure, Fluent English for technical collaboration, Availability for collaboration with US West Coast time zone 📃 Skills: Python, TypeScript, Scala, Java, Kotlin, LLM, OpenAI, Anthropic, API, AWS, GRPC, MySQL, 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. 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. Strong, hands-on experience in at least one of the following: Scala, or another modern JVM language (e.g., Kotlin, Java 17+). 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: Backend Python Engineer role focused on building a desktop control plane for deploying and configuring local AI inference on devices like NVIDIA Spark. The position involves managing model lifecycle, integrating coding agents with locally hosted models, and evolving an internal MVP toward an open-source developer tool. Work includes backend development, LLM proxy routing, Docker lifecycle management, and production-grade API design. 🗂️ Requirements: Strong Python skills, Experience with FastAPI or Flask, Knowledge of asynchronous and concurrent programming, Experience with backend API development, Understanding of Docker lifecycle management, Experience integrating external APIs, Knowledge of LLM proxy routing concepts, Ability to design idempotent endpoints and implement retry mechanisms, Experience with relational databases, Fluent English 📃 Skills: Python, FastAPI, Flask, Asyncio, LiteLLM, Pydantic, PostgreSQL, AWS, Docker, HuggingFace, CUDA, vLLM, Ollama, LLM, API 🏢 Description: VirtusLab is a leading European software consulting and engineering company, home to over 350 EU-based professionals. 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 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 We’re looking for an engineer to join a small, startup-like team building a tool for deploying and configuring local AI inference on local devices like NVIDIA Spark. You’ll work on managing the model lifecycle (start/stop) and connecting coding agents—such as Claude Code, Codex, and others—to locally hosted models. Your daily work will be on the backend: adapting LiteLLM configuration as agent APIs (Claude Code, Codex, etc.) evolve, managing the lifecycle of docker images that ship the agents, integrating with the Hugging Face API for model downloads, and getting the production essentials right—idempotent endpoints, retries with backoff, and straightforward migrations. The team already has an internal MVP and talks directly with potential users. We’re on the road to making it open source. If you want to shape a developer tool from the early stages, this is it. Project Local Inference Platform for Python Engineers Project Scope A desktop application for deploying and configuring local AI inference on local devices (e.g., NVIDIA Spark / DGX Spark), managing model lifecycle (start/stop), and connecting coding agents like Claude Code and Codex to locally hosted models. Currently an internal MVP, on the road to open source. Tech Stack Python, Asyncio, FastAPI, LiteLLM, Pydantic, PostgreSQL, AWS, Agent layer: LLM proxy routing from agents to BE Challenges Building a desktop control plane for local AI agents that abstracts away the messy parts of running LLMs on heterogeneous hardware — model lifecycle, proxy routing, agent configuration, and OS-specific quirks (path separators, signing, packaging) — while keeping the system extensible enough to evolve toward open source. Visualising model statistics and system load on top of a backend that actually does the deployment. Team Small, startup-like team on the JetBrains side — no bureaucracy, direct contact with potential users, fast iteration. Code reviews as part of the process. What we expect in general: Strong Python skills with experience in backend frameworks such as FastAPI or Flask. Solid understanding of concurrent and asynchronous programming. Ability to rapidly prototype and iterate on emerging ideas. Engineering pragmatism: cutting complexity while keeping the system extensible. System-level thinking: understanding how the Docker lifecycle, LLM proxy routing, model management, and the agent layer fit together. Hands-on experience using LLMs daily, with the judgment to know when they help and when they don’t. Self-motivation and the ability to take full ownership of features end-to-end. Fluency in English, with good communication skills for a remote-first team. Nice to have: Experience using Docker for local deployment and service orchestration. Experience setting up and maintaining an LLM proxy layer such as LiteLLM or OpenRouter. Experience with vLLM or ollama. Familiarity with the HuggingFace API and model distribution patterns. Experience with local GPU inference setups (CUDA, NVIDIA hardware) Background working with coding agents (Claude Code, Codex, Aider) and their configurations. 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: 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: 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: 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 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 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

🏢 Summary: The role focuses on building and owning robust data pipelines on a Spark cluster orchestrated with Airflow, while ensuring high data quality, observability, and reliable ML model deployment. You will work with Azure infrastructure using Infrastructure as Code and automate CI/CD workflows to support production-grade ML solutions. The position bridges data engineering and MLOps to deliver scalable, trustworthy systems in a retail loss prevention project. 🗂️ Requirements: Expert-level Python development, Strong experience with PySpark and large-scale data processing, Hands-on experience with Airflow for workflow orchestration, Experience provisioning cloud infrastructure using Infrastructure as Code, Proficiency with Azure or equivalent cloud platforms, Experience building and maintaining CI/CD pipelines with GitHub Actions, Experience with data quality validation and monitoring, Experience with observability and monitoring tools, Ability to productionize and monitor ML models, Advanced English (B2/C1) 📃 Skills: Python, PySpark, Airflow, Azure, Terraform, GitHub, Actions, CI/CD, Spark, 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. 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 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: Design and build a modern Data Platform from scratch for an insurance client, establishing a governed, production-ready Snowflake environment and enabling AI capabilities. The role covers full lifecycle ownership from architecture and data modelling to pipeline implementation and post-launch operations. You will develop scalable data ingestion and processing solutions while promoting best practices, automation, and CI/CD standards. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (Snowflake, BigQuery or Redshift), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design, Experience with cloud platforms (AWS, GCP or Azure), Experience with cloud data services (S3, GCS, ABS, EMR, Dataproc, MWAA, Composer, ADF or AWS Glue), Ability to design and maintain data quality and governance standards, Experience working in Agile environments 📃 Skills: Python, SQL, Snowflake, Databricks, BigQuery, Redshift, Azure, AWS, GCP, Terraform, dbt, Spark, PowerBI, ADF, Glue, EMR, Dataproc, MWAA, Composer 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project JetBrains Projectt scope The client is introducing Atlan as a new internal Data Catalogue solution and uses Glean as a company-wide unified search platform for thousands of employees. To ensure a smooth transition from our existing Knowledge Base and OpenMetadata setup, we need to index Atlan assets into Glean so that metadata for databases, tables, metrics, and reports is easily discoverable through search. Tech stack Python,  System & Data Integration, Kubernetes, System design, Infrastructure mindset Skills We’re looking for a Data Platform Engineer with experience in data platforms and system design at scale. We expect a track record in designing integration architectures for external systems and streamlining data migration/ingestion. As a Data Platform Engineer, you will design and implement a solution that: Periodically indexes Atlan metadata assets into Glean, runs on a configurable schedule (hourly/daily), is production-ready, observable, and maintainable by our DevOps team after handover. Moreover, ensure compliance and data governance at the appropriate level in line with the company’s standards. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t 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! Apply now

🏢 Summary: Design and build a modern data platform from scratch for an insurance client, covering architecture, data ingestion, modelling, and production operations. The role focuses on establishing a governed, scalable Snowflake-based environment to enable reliable reporting and AI capabilities. You will take ownership across the full data lifecycle, from requirements definition to deployment and maintenance. 🗂️ Requirements: Hands-on experience with Python, Proven experience with data warehouse solutions (BigQuery, Redshift or Snowflake), Experience with Databricks or data lakehouse platforms, Strong expertise in data modelling and ETL/pipeline design and maintenance, Experience with AWS, GCP or Azure cloud services, Ability to design and build data ingestion and processing pipelines, Experience working in Agile environment, Understanding of data governance and data quality concepts 📃 Skills: Python, SQL, Snowflake, BigQuery, Redshift, Databricks, Azure, AWS, GCP, Terraform, dbt, PowerBI, Spark, ETL, CI/CD 🏢 Description: We are #VLteam – tech enthusiasts constantly striving for growth. The team is our foundation, that’s why we care the most about the friendly atmosphere, a lot of self-development opportunities and good working conditions. Trust and autonomy are two essential qualities that drive our performance. We simply believe in the idea of ​​“measuring outcomes, not hours”. Join us & see for yourself! About the role The majority of these roles will be at the forefront of client collaboration and building VL positions in the industry (spearheading projects). You will work closely and directly with a different specialist from the client side. Collaborate with stakeholders to define requirements, develop data pipelines and data quality metrics. You will participate in defining the requirements and architecture for the new platform, implement the solution, and remain involved in its operations and maintenance post-launch Your work will also introduce data governance and management, laying the foundation for accurate and comprehensive reporting that was previously impossible. Build data ingestion & processing pipelines. All of the above with a strong focus on the customer’s needs. Flexibility in action and the ability to overcome obstacles are highly valued in this role. View available projects: Project Data Foundation & AI Enablement Project Scope We are architecting a modern Data Platform for a fast-scaling client in the Insurance sector. Our work consolidates fragmented legacy systems, organises data from a vast number of sources, and establishes a standardised, governed, and future-proof data foundation. We aim to unlock the full value of the company’s data, enabling faster, informed decision-making and providing the backbone for business growth and AI readiness. Tech stack SQL, Python, Snowflake, dbt, Data modelling, Data quality, Power BI, Azure, Terraform Challenges The primary objective is to deliver a robust data foundation and enable AI capabilities for a client that has grown organically. The work focuses on several key areas: Establishing a production-ready, fully operational Snowflake environment and driving operational excellence. Translating complex business logic into accurate data models to ensure the platform truly reflects business reality. Integrating diverse data sources to build reliable data products and comprehensive data dictionaries. Managing the full Data Engineering and Data Science lifecycle to support production ML and AI experimentation. Taking ownership from concept to deployment. Cultivating an engineering mindset by promoting automation, CI/CD, and rigorous standards. Team We are building a small (4-6 people), agile, cross-functional team capable of delivering the complete data platform, from initial architecture to production operations. Roles involved: DevOps, Data Engineer, Snowflake Specialist, MLOps/AI Engineer, Business Analyst (BA). The team will collaborate closely with business stakeholders to ensure effective knowledge transfer and strict alignment with strategic goals. Team The team is small but highly motivated, taking on a broad scope of responsibilities as the platform is built and expanded. What we expect in general A proactive approach and flexibility in action were a must Very good command of English (written and spoken) Hands-on experience with Python Proven experience with data warehouse solutions (e.g., BigQuery, Redshift, Snowflake) Experience with Databricks or data lakehouse platforms Strong background in data modelling, data catalogue concepts, data formats, and data pipelines/ETL design, implementation and maintenance Ability to thrive in an Agile environment, collaborating with team members to solve complex problems with transparency Experience with AWS/GCP/Azure cloud services, including: GCS/S3/ABS, EMR/Dataproc, MWAA/Composer or Microsoft Fabric, ADF/AWS Glue Experience in ecosystems requiring improvements and the drive to implement best practices as a long-term process Experience with Infrastructure as Code practices, particularly Terraform, is an advantage Proactive approach Don’t worry if you don’t 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! Apply now