Python & MLOps Engineer

🏢 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: 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: 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: 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: 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: Engineering role focused on building a cross-platform desktop application for managing and deploying local AI inference models, using Kotlin and Compose Desktop. The position involves creating UI, integrating with REST APIs, configuring AI agents, and handling packaging for Windows, macOS, and Linux. It offers the opportunity to shape an early-stage developer tool evolving toward open source. 🗂️ Requirements: Strong Kotlin proficiency, Experience with Compose Desktop, Knowledge of asynchronous and concurrent programming with Coroutines, Experience integrating with REST APIs, Understanding of cross-platform desktop development differences, Ability to manage and parse TOML/JSON/YAML configuration files, Experience building or packaging desktop applications for Windows, macOS, and Linux, Understanding of LLM workflows and local model deployment 📃 Skills: Kotlin, Compose, Coroutines, REST, TOML, JSON, YAML, LLM, MSI, DEB, DMG, mitmproxy, LiteLLM, OpenRouter 🏢 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 desktop tool for local AI inference. You’ll work with Kotlin and Compose Desktop to create an application that deploys, configures and manages AI models running on local devices – think NVIDIA Spark, Claude Code, and Codex connected to locally hosted models. Your daily work will include building the UI in Compose Desktop, integrating with backend REST APIs for model deployment, and setting up agent configurations through TOML/JSON/YAML files. You’ll also work on LLM proxy routing and create installers for Windows, macOS and Linux. 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 Project Scope We are building a desktop application for deploying and configuring local 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 Kotlin, Compose Desktop (with JetPack Compose roots), kotlinx.coroutines Backend integration: REST APIs for model deployment management Agent layer: configuration files in toml/json/yaml, LLM proxy routing from agents to BE Packaging: native installers — msi (Windows), deb (Linux), dmg (macOS) Nice-to-have tooling: mitmproxy for HTTP debugging, LiteLLM/OpenRouter-style proxy layers. 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 Kotlin skills and genuine interest in Compose Desktop as a UI framework Understanding of asynchronous and concurrent programming with Kotlin Coroutines Awareness of cross-platform differences (file paths, OS-specific packaging) Engineering pragmatism: cutting complexity while keeping the system extensible System-level thinking: understanding how UI, backend APIs, agent configs and proxy layers fit together Hands-on experience using LLMs daily, with the judgement to know when they help and when they don’t Fluency in English, with good communication skills for a remote-first team Self-motivation and the ability to take full ownership of features end-to-end Experience with different LLM agents and their configurations (nice to have) Experience with mitmproxy or similar HTTP traffic inspection tools (nice to have) Experience with LLM proxy layers such as LiteLLM or Openrouter (nice to have) Experience creating and signing OS installers (MSI, DEB, DMG – nice to have) 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 a Bazel-focused Developer Advocate combining consulting, development, and community engagement. The role involves leading Bazel migrations, building open source and internal tooling, and supporting pre-sales and training activities. It blends hands-on engineering with technical advocacy around build systems and SDLC practices. 🗂️ Requirements: 3+ years experience in backend, DevOps, or platform engineering, Experience with build tools and CI/CD systems, Practical experience with Bazel or another build tool, Strong knowledge of at least one ecosystem (JVM, C++, Rust, Go, NPM), Experience in developing and maintaining SDLC processes, Ability to work with C++ codebases, Experience in technical mentoring or training 📃 Skills: Bazel, Starlark, C++, CI/CD, JVM, Rust, Go, NPM 🏢 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 Project scope This role is focused on a mixture of consult and dev-rel work around Bazel. This means a mix of:– doing Bazel migration– promoting Bazel and our expertise through conferences, meetups, blog posts, and Social Media– developing open source and internal solutions focused on Bazel– pre-sales and consultancy work– training and mentoring developers on Bazel This role usually is connected with part-time work within other projects related to Bazel. Tech stack Bazel, Starlark, C++ Challenges This position requires exceptional skills in multitasking. It requires a willingness to public speaking, write articles, and activity within Social Media or discussion forums (e.g., Bazel Slack). It requires a lot of initiative and creativity. Team 2 developer advocate/experts. What we expect in general 3+ years of experience in backend, devops, or platform engineering Some experience in developing solutions around building tools, maintaining CI/CD, and other aspects of SDLC Some experience of Bazel or at least one other build tool. Candidate should know well at least one ecosystem (JVM, C++, Rust, GoLang, NPM etc.) Communication skills and a pragmatic approach to problem-solving Ability to work as a part of a team Pro-active approach to problem-solving, without hesitation in reaching out for help Being self-driven and self-managing tasks 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 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!