April 29, 2026

Kotlin Desktop Engineer – AI Inference Tooling (Senior/Staff)

Senior • Remote

21,000 - 31,080 PLN

Krakow, Poland

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!

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Krakow, Poland

15,000 - 22,000 PLN

🏢 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!

Technology

VirtusLab

Software Engineer with ML and Data Skills

Senior

Remote

Krakow, Poland

140 - 185 PLN

🏢 Summary: Opportunity to productionize and scale an ML-driven data quality system (Anomalsky) on GCP, combining classic ML and LLM reasoning to detect and explain row-level data anomalies. The role focuses on building anomaly detection and clustering pipelines, integrating them into acquisition workflows, and developing a real-time validation layer. You will collaborate with data engineers and product teams to operationalize models and continuously improve data quality at scale. 🗂️ Requirements: Strong Python and production ML experience, Experience deploying ML models into production pipelines, Hands-on experience with unsupervised anomaly detection (kNN, Isolation Forest, autoencoders), Experience with clustering on large-scale tabular data, Experience combining classic ML with LLMs for reasoning and validation, Experience with Airflow and Spark (Dataproc), Experience with BigQuery and Snowflake, Experience with Iceberg and Trino/Starburst, Experience with GCP and Docker, Experience with Terraform and CI tools, Experience with MLflow, Professional English proficiency 📃 Skills: Python, Airflow, Spark, Dataproc, BigQuery, Snowflake, Iceberg, Trino, Starburst, AWS, GCP, Docker, Terraform, Jenkins, GitHub, Scikit-learn, MLflow, kNN, IsolationForest, Autoencoders, Clustering, LLM 🏢 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 Productionizing and scaling an ML-driven data quality system across the organization. The scope of services involves: building and tuning anomaly-detection and clustering pipelines, pairing classic ML with LLM reasoning to flag and explain issues, collaborating with data producers to fix root causes, and creating as well as maintaining validator models that turn detected anomalies into better future data. Python Expert Airflow Advanced Spark (Dataproc) Advanced Scikit-learn Advanced Apache Iceberg Advanced BigQuery Regular Snowflake Regular Trino/Starburst with Iceberg Regular AWS / GCP Regular GitHub Actions Regular Jenkins Basic Terraform Basic Docker Basic View available projects Project Anomalsky Project Scope Our client is a NASDAQ-listed B2B data company powering Go-To-Market strategies with a 360-degree view of every customer, a view whose value depends on the quality of billions of person and company records. Anomalsky is the ML system built to catch what traditional observability misses: row-level semantic anomalies (e.g., a first_name, title, company_name). Three layers, an ML layer (embeddings + unsupervised clustering) flags suspicious records at scale, an LLM layer removes false positives and explains each cluster, and an optional human-in-the-loop lets domain experts resolve whole clusters at once. The MVP already drove ~40k crucial record corrections in production. What’s next: the MVP is landing on GCP now. Once it’s operational, the mission is to scale Anomalsky across the entire organization, embedding it into Acquisition pipelines and building a real-time variant that scans data before it reaches customers. The scope of cooperation covers Productionizing Anomalsky on GCP and scaling it to operational, organization-wide use. Evolving the ML / LLM / human-in-the-loop design and the feedback loop that turns expert reviews into reusable knowledge. Prototyping the low-latency real-time variant. Integrating Anomalsky into existing workflows, starting with Acquisition. Tech Stack Python, Airflow, BigQuery, Snowflake, Spark (Dataproc), Databricks, Iceberg, Starburst, Trino, AWS, GCP, Docker, Terraform, Jenkins, GitHub, Scikit Learn,  unsupervised anomaly detection (kNN, Isolation Forest, autoencoders), recursive clustering, classifiers on real + synthetic data, MLflow, LLM-based reasoning. Project environment ML and data engineers from VirtusLab collaborating with customer data engineers and product management. What we expect in general Strong Python and production ML skills, with a proven track record of shipping models into real production pipelines. Hands-on experience using classic ML to surface data quality issues at scale: unsupervised anomaly detection (kNN, Isolation Forest, autoencoders) and clustering on messy real-world tabular data. Practical experience pairing classic ML with LLMs: using models to flag suspicious records and LLMs for reasoning, false-positive filtering, and the final verification of anomalies. Solid data engineering background across the modern stack (Airflow, Spark/Dataproc, BigQuery, Snowflake, Iceberg/Trino) and the production toolchain (GCP, Docker, Terraform, CI, MLflow). Pragmatic, product-oriented approach focused on incremental value delivery and seamless integration into existing workflows. Professional fluency in English, enabling smooth technical and business discussions in an international environment. 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

Technology

VirtusLab

Python Engineer with MLOps

Senior

Remote

Krakow, Poland

140 - 170 PLN

🏢 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!