Job Overview

We are seeking a marketing analytics professional with a focus on data quality and AI-driven automation to improve marketing measurement, reporting, and decision-making. This role combines marketing analysis, data operations, and applied AI to ensure trusted, consistent data across multiple sources and to automate dashboards, attribution insights, and scalable analytical workflows.

Reports to

• Team Lead of Data & Marketing Technology

What will you do?

• Analyze marketing channels performance and deliver actionable recommendations
• Build and automate KPI reporting
• Support and automate experiment measurement (A/B, incrementality, creative testing)
• Design AI-powered automations for reporting, insight generation, anomaly detection, and campaign recommendations
• Own marketing/attribution data quality across sources (AppsFlyer + ad platforms), including validation and tracking troubleshooting
• Develop and maintain predictive models
• Partner with marketing, product, and engineering on tracking requirements, measurement plans, and documentation.
• Help maintain data pipelines/semantic layers; ensure metric definitions and transformation logic are clean and well-documented

What are we looking for?

• STEM education
• Strong foundation in marketing analytics: attribution, funnels, cohort/retention, LTV, ROAS/CAC, experimentation
• Hands-on experience with data analysis and automation (SQL + Python, BI tools, workflow automation)
• Familiarity with mobile attribution/measurement platforms (e.g., AppsFlyer) and multi-source marketing data integration
• Proactive mindset and eagerness to grow practical AI skills (ML fundamentals, LLM tooling, data quality automation)

What additional skills will help you stand out?

• Experience with warehouses (BigQuery/Snowflake), dbt, Airflow, or similar
• Experience with SKAdNetwork and privacy-safe attribution
• Experience operationalizing LLM workflows (prompting, evaluation, guardrails) for analytics use cases
• Experience with predictive modeling techniques (e.g., regression/classification, time-series forecasting, uplift/propensity modeling) and model evaluation

Work mode

• Hybrid (2-3 days of work from the office) 
• This role is eligible for relocation & immigration support.

Benefits

Benefits and perks are tailored to the local market and culture. Our benefits in Belgrade include:

• Additional vacation days based on years of service at Wargaming: up to 5 days on top of the statutory minimum
• Additional paid time off (5 Personal Days, Birthday Leave, Marriage Leave, Compassionate Leave)
• Sick Leave Compensation, Maternity Leave Benefits  
• Premium Private Health Insurance
• Career development and education opportunities within the company
• English clubs and platform for learning languages
• Mental well-being program (iFeel)
• Commuting allowance
• Company events
• FitPass membership
• Discounts for employees
• Personal Gaming Account
• Coffee, fruits, and snacks in the office
• On-site canteen with subsidized prices for food and drinks
• Seniority Awards
• Referral program - you can recommend the best talents to the Company and receive a reward

Please submit your CV in English to ensure smooth processing and review.

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are now building services and agentic tools that provide AI coding agents and end users with deeper context about codebases. Our code retrieval service already delivers meaningful improvements in agent speed and task performance, and we aim to push this further – extracting richer insights than snippets alone at the scale of several hundred thousand repositories. 

We are looking for an AI Engineer who can design and implement agentic tools from scratch, bring them to the end users, and make coding with agents smarter, faster, and more reliable.

In this role, you will:

• Translate product needs into agentic tools and services and ship them to production.
• Scale prototypes to large numbers of users.
• Improve and test our semantic search service.
• Build evaluation pipelines for code retrieval and coding task performance.

We’ll be happy to have you on our team if you have:

• At least five years of hands-on NLP experience.
• Experience in information retrieval systems.
• Strong experience in LLM prompt and tool engineering, as well as with AI agents.
• Solid programming skills in Python and/or Kotlin (and the willingness to learn the language you’re unfamiliar with).
• Experience building and operating production-grade software systems.

We’d be especially thrilled if you have:

• Experience developing in Kotlin or Java.
• Previously worked with code intelligence (e.g. AST, symbol graphs).

#LI-DNI

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior ML Researcher to develop the core methods that make Spectrum possible – novel approaches to temporal ontology extraction, contradiction detection, and semantic alignment across heterogeneous software artifacts. You will help define and execute the research agenda, while also collaborating with JetBrains Research and external academic advisors.

Your responsibilities will include:

• Developing methods for LLM-based ontology construction from code, documentation, and issue trackers, including contradiction detection and reasoning over the resulting knowledge graph.
• Creating datasets, metrics, and benchmarks that drive measurable improvements across the system.
• Prototyping and validating research ideas, then collaborating with ML and software engineers to bring them to production.
• Collaborating with JetBrains Research and external academic advisors to shape our research agenda.
• Publishing research findings at top venues and representing Spectrum in the research community.

We expect you to have:

• A PhD (or equivalent research experience) in NLP, knowledge graphs, ontology learning, information extraction, or a closely related field.
• A strong publication record in at least one of the following areas: knowledge graph construction, ontology learning, information extraction, or NLP.
• Experience applying LLMs to structured knowledge extraction tasks.
• Experience designing and running rigorous experiments, including hypothesis formulation, ablation studies, and statistical evaluation.
• Strong Python and PyTorch skills, with the ability to implement research ideas from scratch.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontology engineering, semantic web technologies (OWL, RDF, SPARQL), or ontology alignment.
• A background in code analysis, developer tools, or software engineering research.
• Experience with knowledge graph embedding methods or graph neural networks.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• Actively contributed to relevant open-source projects.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• Full support for publishing ML research and attending industry conferences.
• Collaboration with JetBrains Research and external academic advisors in the knowledge graph and ontology learning community.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• A rare applied research role where your methods ship in a real product used by software teams.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

The Python Ecosystem team builds PyCharm – one of the most popular Python IDEs in the world – along with the Python plugin for IntelliJ IDEA. As AI changes how developers write, debug, and ship code, we’re making our Python tools AI-native. We’re looking for an AI Lead to drive this effort by shaping the architecture, building key components hands-on, and guiding the team in making strong decisions around AI-powered product development.

In this role, you will:

• Lead the technical design of AI features in PyCharm and our Python tooling, including MCP integrations, agent workflows, tool design, and context management.
• Prototype and ship features yourself – this is a hands-on technical leadership role.
• Help the team adopt AI technologies effectively by providing technical guidance, reviewing approaches, and sharing practical patterns.
• Evaluate emerging AI tools, frameworks, and providers, and make pragmatic decisions about what to build and what to integrate.
• Work closely with product managers, ML engineers, QA specialists, and senior developers to turn product ideas into solid technical plans.
• Navigate a large Kotlin/Java codebase and expose IntelliJ Platform capabilities – such as code analysis, inspections, refactorings, and type inference – to AI-powered workflows.
• Contribute to cross-team AI efforts and help define shared engineering patterns where appropriate.

We’d love to talk to you if you have:

• Strong software engineering experience, particularly in Python and/or Kotlin/JVM.
• Deep, hands-on familiarity with modern AI tooling for developers, including coding assistants, agents, MCP, and LLM-based workflows.
• Experience working in large, mature codebases and delivering meaningful technical change without compromising quality.
• Familiarity with LLM evaluation and benchmarking.
• A track record of making good technical decisions in fast-moving, ambiguous areas like proposing architectures, building prototypes, and iterating based on feedback.
• Strong communication skills and the ability to influence technical direction without formal authority.
• A strong product sense and care about solving real user problems, not just building interesting technology.

Nice to have:

• Experience with IDE or developer tooling internals, such as language servers, code analysis, or related systems.
• Experience with the Python AI/ML ecosystem.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. (keep if relevant for the role)
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI 

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. 

Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
• Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
• Establishing MLOps practices, including orchestration, observability, and experiment tracking.
• Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
• Defining hiring criteria, growing the ML team, and shaping the ML team culture.

We expect you to have:

• A proven track record as an ML/AI Lead.
• At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
• Vector databases and retrieval-augmented generation (RAG) patterns.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal. 

Our ideal candidate would have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• The ability to think strategically about product-led AI, beyond just training models in isolation.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.

#LI-KP1

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior AI/ML Engineer to build and evolve the ML-powered systems at the heart of our product.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
• Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving AI agents, which will involve prompt engineering, model selection, and inference optimization.
• Contributing to our MLOps practices, including orchestration, observability, and experiment tracking.

We expect you to have:

• At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangGraph, Pydantic AI, or an equivalent.
• Retrieval-augmented generation (RAG) patterns and vector databases.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• Opportunities to publish research at top venues in collaboration with JetBrains Research.

#LI-DNI

About the role:

ABBYY Vantage is our flagship Document AI platform – a cloud-native, microservices-based product that combines purpose-built AI, OCR, NLP, and direct LLM integration to help enterprise customers extract, classify, and act on data from any document. Vantage 3.0, our latest release, introduces native Azure OpenAI integration, enterprise-grade compliance and redaction, a real-time analytics dashboard, and a growing library of pre-configured AI skills. Over 10,000 customers trust ABBYY – including Fortune 500 companies like DHL, Johnson & Johnson, FDA, PwC, KeyBank, Spotify, and H&R Block – to automate their most complex document workflows.

We are looking for a Staff Software Engineer to serve as a senior technical leader on the Vantage platform. You will drive the design and delivery of complex, cross-cutting capabilities – spanning document AI pipelines, LLM integrations, compliance infrastructure, analytics, and platform extensibility. Beyond your own code, you will act as a technical multiplier: influencing architectural decisions, setting quality standards, and developing the engineers around you. This is a role for someone who leads through depth, judgment, and impact.

Job Responsibilities:

• Technical Leadership: Drive the technical design and delivery of significant Vantage platform capabilities, from architecture and API contracts through deployment, monitoring, and iteration.
• Quality & Standards: Define and uphold engineering standards for the Vantage codebase – covering code quality, service reliability, performance, security, and compliance – and drive their adoption across teams.
• Strategic Collaboration: Act as a senior technical voice in cross-functional planning with product management, ML engineering, cloud architecture, and engineering leadership; translate business priorities into actionable technical roadmaps.
• Platform Improvement: Lead initiatives to improve Vantage platform health at scale: service decomposition, observability, CI/CD maturity, and developer productivity.
• Operational Excellence: Own high-severity incident response for Vantage cloud services; drive post-mortems and systemic reliability improvements.
• Engineering Mentorship: Mentor Senior and Principal Engineers on the Vantage team; build a culture of technical rigor, shared ownership, and continuous learning.
• Technical Innovation: Evaluate and champion adoption of new technologies – from GenAI model integrations to cloud-native tooling – that strengthen ABBYY's Document AI differentiation.

Job Requirements:

• 10–13 years of professional software engineering experience with deep expertise in C# .NET and C++, willing to work with both languages
• Proven experience designing, implementing, and operating CI/CD pipelines for building, testing, and deploying workflows using GitHub Actions and/or Azure DevOps Pipelines
• Strong command of microservices architecture, distributed system design, and cloud-native patterns at enterprise scale
• Demonstrated ability to mentor Senior and Mid-level Engineers and partner with Engineering Managers on technical direction
• Experience leading technical design reviews and influencing architectural decisions across team and product boundaries

Desired Qualifications

• Experience in cloud, preferably using Microsoft Azure (AKS, Storage, Key Vaults, Azure SQL or equivalent)
• Track record of delivering production-grade systems that meet enterprise compliance, security, and reliability standards
• Hands-on experience designing and operating workflow-driven systems (orchestration, retries, timeouts, and state management)
• Experience integrating Machine Learning, Neural Networks or LLMs into enterprise applications and workflows
• Comfort operating across a globally distributed engineering organization spanning multiple regions and cultures

About the role:

ABBYY Vantage is our flagship Document AI platform – a cloud-native, microservices-based product that combines purpose-built AI, OCR, NLP, and direct LLM integration to help enterprise customers extract, classify, and act on data from any document. Vantage 3.0, our latest release, introduces native Azure OpenAI integration, enterprise-grade compliance and redaction, a real-time analytics dashboard, and a growing library of pre-configured AI skills. Over 10,000 customers trust ABBYY – including Fortune 500 companies like DHL, Johnson & Johnson, FDA, PwC, KeyBank, Spotify, and H&R Block – to automate their most complex document workflows.

We are looking for a Senior Software Engineer to join the Vantage engineering team. You will be a hands-on contributor building and evolving the services that power Vantage's document AI capabilities – from OCR pipelines and skill training workflows to API integrations and analytics infrastructure. You bring strong engineering fundamentals, a quality-first mindset, and a drive to deliver reliable, scalable software in a cloud-native environment.

Job Responsibilities:

• End-to-End Development: Design, develop, test, and deploy features and services within the Vantage platform, contributing to areas such as document processing pipelines, AI skill management, cloud infrastructure, and API layers.
• Code Quality: Write clean, maintainable, well-tested code; actively participate in code reviews and champion engineering best practices across your team.
• Cross-Functional Collaboration: Work closely with product managers, UX designers, ML engineers, and fellow software engineers to translate Vantage feature requirements into well-architected solutions.
• Continuous Improvement: Identify and surface improvements to existing Vantage services, tooling, and delivery workflows; contribute to reducing technical debt and increasing engineering velocity.
• System Reliability: Monitor the health and performance of Vantage cloud services; investigate and resolve production incidents in a timely manner.
• Technical Growth: Stay current with advances in Document AI, cloud-native patterns, and GenAI integration approaches that could enhance the Vantage platform.

Job Requirements:

• 5–9 years of professional software engineering experience with deep expertise in C# .NET and C++, willing to work with both languages
• Proven experience designing, implementing, and operating CI/CD pipelines for building, testing, and deploying workflows using GitHub Actions and/or Azure DevOps Pipelines
• Good understanding of microservices architecture, distributed system design, and cloud-native patterns at enterprise scale
• Demonstrated track record of delivering high-quality, testable code
• Strong analytical and debugging skills with the ability to investigate complex issues across distributed systems

Desired Qualifications

• Experience in cloud, preferably using Microsoft Azure (AKS, Storage, Key Vaults, Azure SQL or equivalent)
• Hands-on experience designing and operating workflow-driven systems (orchestration, retries, timeouts, and state management)
• Experience integrating Machine Learning, Neural Networks or LLMs into enterprise applications and workflows
• Familiarity with OCR, NLP and computer vision technologies
• Comfort operating across a globally distributed engineering organization spanning multiple regions and cultures

At JetBrains, code is our passion. Ever since we started back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production and free developers to focus on creativity and problem-solving.

The IntelliJ AI team develops the AI-specific core of JetBrains IDEs. We work on agentic workflows, intelligent editing assistance, and new AI-powered capabilities that redefine how developers interact with the IDEs.

We are looking for a Senior Software Developer to help us build the next generation of AI-powered features in JetBrains IDEs.

In this role, you will:

• Integrate state-of-the-art AI agents into our IDEs, continuously improving the developer experience of working with them.
• Enhance agent capabilities by equipping them with the most intelligent tools available in our IDEs.
• Create novel AI features with no direct market analogues, experimenting with and exploring the new possibilities brought by modern AI technologies.
• Measure and evaluate the performance of agents and other AI features to achieve reliability and reproducibility.

We are looking for engineers who:

• Want to help build the best IDEs in the world and push the boundaries of developer tools.
• Have strong knowledge of Java, Kotlin, or similar languages.
• Are comfortable designing and developing complex software systems.
• Are self-driven and able to take end-to-end ownership of challenging features.
• Possess strong communication skills in English, both written and verbal.

Experience that would be especially valuable:

• Building AI-powered features, especially with LLM-based systems.
• Developing IDEs, code editors, or complex desktop applications.
• Working on performance-sensitive or correctness-critical systems.
• Concurrent programming and performance optimization.

Why join JetBrains?

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family.
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible.
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.
  *Some benefits may vary depending on location.

#LI-IM1

Kineto is a next-generation platform that enables creators, educators, and small businesses to generate, deploy, and operate fully functional AI-powered web applications – instantly and at scale. It combines LLM-driven code generation, multi-tenant Postgres (Neon), dynamic hosting (GKE and Knative), automated deployments (Flux), analytics, billing, and a seamless chat-based UX to make software creation accessible to everyone. Our team is growing rapidly, and we’re now seeking an experienced Infrastructure Engineer who can design, build, and maintain our cloud-native platform, with a focus on scalability, reliability, and automated operations.

What you’ll do:

Cloud and platform engineering (DevOps):

• Design, implement, and manage the core infrastructure powering Kineto's platform on Google Cloud Platform (GCP), including networking, security, and identity management.
• Build and operate resilient, highly available distributed systems using Kubernetes (GKE), Knative, Istio, and related cloud-native technologies.
• Automate the entire infrastructure life cycle (IaC) using Terraform and Terragrunt, ensuring secure, reproducible, and auditable environments.
• Implement and maintain CI/CD pipelines (e.g. GitHub Actions and TeamCity) and deployment tools like Flux and Helm for GitOps-driven application delivery.
• Optimize and manage the multi-tenant data layer on Postgres and Neon, focusing on robust tenant isolation, performance, backups, and safe schema management.

Operational excellence and reliability:

• Drive site reliability engineering (SRE) practices, including monitoring, alerting (Prometheus, Grafana), logging (Loki), and incident response.
• Solve complex operational challenges, such as optimizing scale to zero for cost efficiency, minimizing cold starts, enhancing autoscaling behavior, and managing queue backpressure.
• Implement platform-wide performance tuning (e.g. container resource limits, distributed locks, caching strategies, and GC configurations).
• Ensure platform security and compliance by implementing best practices for secrets management, network segmentation, and vulnerability scanning.

Technical leadership:

• Own major infrastructure roadmap items, including multi-region deployments, disaster recovery planning, advanced tenancy separation, and ephemeral preview environments.
• Champion DevOps and SRE principles across the engineering team, mentoring engineers on cloud-native best practices, operational readiness, and debugging complex distributed systems.
• Collaborate with product and engineering teams to define the long-term vision for the platform's architecture and operational model.

We’d be glad to have you on our team if you:

• Have five or more years of experience building and operating large-scale, commercial cloud-native infrastructure, with a strong focus on DevOps/SRE practices.
• Possess deep, hands-on expertise with GCP (or AWS/Azure) and Kubernetes administration and operations (GKE experience is a strong plus).
• Are proficient with infrastructure-as-code (IaC) tools, particularly Terraform, for managing complex environments.
• Have a solid understanding of Linux internals, networking (CNI and service mesh), security, and distributed system design.
• Are familiar with CI/CD tools, GitOps (e.g. Flux), monitoring stacks (Prometheus/Grafana), and logging systems.
• Thrive in cross-functional teams and excel at communicating complex infrastructure ideas clearly.

#LI-YY1

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.

By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.

As part of our team, you will:

• Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
• Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
• Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
• Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
• Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
• Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.

We’ll be happy to have you on our team if you have:

• Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
• A solid understanding of the ML lifecycle from idea to the customer-facing application.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
• Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
• At least three years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
• Developing infrastructure components and services using cluster solutions like Kubernetes.
• The development of Python-based backend services.
• Creating and maintaining ML pipelines, including legacy ones.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
• Writing and maintaining Python libraries used by internal (or external) ML engineers.
• A strong theoretical background in NLP and transformer-based approaches.
• Writing code in Java and/or Kotlin.

#LI-HYBRID
#LI-MR1

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.

We’re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you’ll be responsible for the models, training loops, and evaluation pipelines that power these agents.

You’ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.

As part of our team, you will:

• Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
• Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
• Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
• Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
• Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
• Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
• Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features. 

We’ll be happy to bring you on board if you have:

• Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
• Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
• Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A product-aware mindset – you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.
• At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.
• Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.
• Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
• AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.
• Inference optimization and serving optimized models in production.

#LI-KP1

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

AI features in JetBrains IDEs, developed by the IntelliJ AI team, have quickly become a core part of how developers work inside our IDEs. The IntelliJ AI team partners with product groups across JetBrains to embed advanced AI features that accelerate developer workflows and deliver real value to software engineers.

We are currently looking to hire a Senior Machine Learning Engineer to help us realize our ambitious vision of creating AI assistance that supports the entire development lifecycle across JetBrains IDEs. If selected, you will join the ML subteam within IntelliJ AI, driving the development of our ML system from end to end by defining evaluation and metrics, shaping context orchestration, and helping product teams tailor AI capabilities to their needs.

In this role, you will:

• Design and drive evaluation frameworks for AI features, including metrics, experiments, and agent trace analysis.
• Diagnose model performance issues (e.g. prompt drift, context mismatches, and latency/quality trade-offs) and translate findings into actionable improvements.
• Experiment with contexts and lightweight models to continuously develop our ML system.
• Act as the ML liaison for product teams across JetBrains, adapting and scaling AI capabilities in JetBrains IDEs to their needs.
• Build and maintain small helper models (e.g. re-rankers, classifiers, embedding models) to support domain-specific tasks.
• Collaborate with colleagues in ML, product, engineering, and analytic teams to deliver improvements and monitor their impact in production.
• Stay up to date with research in the fields of LLMs, agents, and evaluation, bringing best practices into our workflows.
• Mentor junior engineers and help shape team culture, processes, and tooling around experimentation and evaluation.

We’d be happy to have you on our team if you: 

• Have 5+ years of experience as an ML Engineer, with a solid background in production-grade ML systems (especially LLMs and agent architectures).
• Have experience with LLM evaluation methods and frameworks.
• Can design and run end-to-end experiments – hypotheses, metrics, data collection (including traces/logs), analysis, and decision-making.
• Are skilled in context-aware pipelines or conversational/agent systems.
• Have strong Python programming skills.
• Bring hands-on experience in fine-tuning or training smaller models (e.g. domain-specific fine-tuning and lightweight customizations).
• Communicate clearly and effectively across teams, translating ML/AI insights into product features.
• Have prior mentorship experience with ML/evaluation engineers.
• Thrive in a cross-functional, fast-moving environment, taking ownership, iterating quickly, and delivering results.

We’d be especially thrilled if you have: 

• Familiarity with agent-based systems and orchestrating multi-step reasoning agents.
• Experience with the Kotlin programming language.

#LI-MR1

At JetBrains, code is our passion. Ever since we started, back in 2000, we've been striving to make the strongest, most effective developer tools on earth. Today, AI-powered coding agents are becoming a core part of how developers write Kotlin – and we want to make sure they write it well.

The Kotlin AI Value Stream team is responsible for how AI agents understand, generate, and improve Kotlin code across all platforms: Android, Kotlin Multiplatform, server-side, web, desktop, and others. We build the evaluation infrastructure, error analysis tools, and post-training pipelines that measure and improve agent behavior on real Kotlin developer tasks.

As a Research Engineer on this team, you'll own the end-to-end loop: Analyze how agents fail on Kotlin → build evals that capture those failures → research and implement methods to fix them → measure the improvement. Your work will directly shape how millions of developers experience Kotlin through AI coding agents.

As part of our team, you will:

Build tools for agentic error analysis

• Design and implement tooling to systematically capture, classify, and analyse errors that AI coding agents make when generating Kotlin code.
• Build observability pipelines over agentic traces – mining patterns from agent sessions in JetBrains IDEs, Junie, Claude Code, Cursor, and other coding agents.

Build evaluation pipelines

• Design, implement, and maintain evaluation pipelines that measure Kotlin code generation quality across dimensions, including correctness, idiomaticity, build success, framework usage, and test coverage.
• Build simulation environments where coding agents can be measured on realistic Kotlin developer tasks – from greenfield KMP projects and Gradle dependency management to migrating Spring applications from Java to Kotlin.
• Own evaluation infrastructure: metrics, experiment tracking, automated regression checks, and reproducible benchmarking.

Research methods for improving agent and model behavior on Kotlin

• Experiment with post-training techniques (SFT, DPO, GRPO) to improve how models handle Kotlin-specific patterns, idioms, and frameworks.
• Investigate context engineering approaches: CLAUDE.md/AGENTS.md files, compiler-as-verifier feedback loops, Kotlin LSP integration, and MCP-based tooling.
• Run experiments to measure impact: A/B comparisons, benchmark suites, and before/after analyses on real codebases.
• Collaborate with model providers (Anthropic, OpenAI, and Google) to translate Kotlin-specific findings into model improvements.

Build public Kotlin benchmarks

• Design and build open-source benchmarks that measure AI coding agent performance on Kotlin tasks and eventually become the standard reference for the ecosystem.
• Create task datasets covering the breadth of Kotlin usage: the server side (Spring, Ktor), multiplatform projects (KMP), build systems (Gradle), Android, library development, and others.
• Include both mined real-world tasks and carefully designed synthetic tasks that test specific Kotlin capabilities.
• Maintain and evolve benchmarks as models improve, ensuring they remain challenging, relevant, and contamination-resistant.

We'll be happy to have you on board if you have:

• Hands-on experience building evaluation or analysis pipelines for LLMs or AI coding agents in a research or production setting.
• Strong Python engineering skills (at least three years), with the ability to write clean, maintainable code in data-heavy and ML-adjacent codebases.
• Experience with data analysis at scale: querying large datasets (SQL/Athena), building data pipelines, and performing statistical analysis of experimental results.
• The ability to own projects end to end – from identifying a problem in agent traces to designing an eval, running experiments, and shipping a fix.
• A product-aware mindset: You care about how agents are actually used by developers and can translate real failure modes into evaluation and training work.
• Familiarity with Kotlin or a strong willingness to develop deep Kotlin expertise (you'll be living in Kotlin codebases daily).

Our ideal candidate would also have experience with:

• Post-training LLMs: SFT, RLHF, DPO, GRPO – either hands-on training or designing the data and reward pipelines that feed into training.
• Modern deep learning frameworks (PyTorch) and LLM training stacks (TRL, verl, Megatron, or similar).
• AI agent development: tool-using agents, multi-step coding workflows, agentic frameworks.
• Evaluation frameworks and tools: Inspect AI, Promptfoo, LM-evaluation-harness, or custom eval pipelines.
• Experiment tracking and observability: Weights & Biases, MLflow, Langfuse, or similar.
• The Kotlin ecosystem: Android, Gradle, KMP, Spring, Ktor – with an understanding of the developer workflows that agents need to support.
• Contributing to or maintaining open-source projects, especially benchmarks or evaluation tools.

Don't check every box? That's okay – if you're excited about this work and bring strong fundamentals, we'd love to hear from you. We're happy to talk and provide the training you need to grow into the role.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. 
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

WongDoody creates human experiences at 22 studios across 4 continents. We believe the future can be molded. And by shaping human experiences through creativity and tech, we work to build a future we believe in. 

For us, this starts with our own culture. We strive to create an inclusive environment where every human can bring their whole self to work. Our clients are brands we believe in, from global big players to local heroes to startups we love. With each of our partners, we embark on a journey of co-creation, pushing the boundaries of what's possible and exploring the space where creativity and tech meet. 

Our team of fun, welcoming, values-driven, and collaborative problem solvers has one focus at the heart of everything we do: human experience. Human experiences are the touchpoints where brands connect with customers. And we transform businesses by creating engaging, inspiring moments using strategy, creativity, data and technology - all backed by the global technological power of Infosys. 

Experience, Tech & AI 

We are a cross-unit and cross-location AI, tech and experience team. With more than 50 developers, AI & Full Stack engineers, UX designers and consultants working directly with other WongDoody teams, we are team players and specialists - oth in frontend and backend. As part of Infosys, we belong to a leading global technology company with access to solutions and extensive know-how in the fields of commerce, marketing automation and AI, among others.  

Now we’re looking for an AI Engineer who connects creativity, technology, and intelligence to bring agentic and visual AI experiences to life. 

Our local benefits 

• Flexible working hours and 100% overtime compensation
• Work where it works for you. At home or in the office, or any mix you like 
• Working for strong brands and clients we believe in 
• 26 days vacation per year 
• Nice people in welcoming teams 

What you can expect 

• Design and engineer agentic and multimodal AI systems that bring together creativity, data, and automation 
• Develop end-to-end GenAI workflows that integrate LLMs, visual AI systems (via ComfyUI), and existing enterprise stacks 
• Connect and orchestrate visual generation interfaces with backend systems and APIs for marketing, design, and content production use cases 
• Prototype, validate, and scale AI-driven experiences from concept to production (together with designers, strategists, and engineers)
• Define AI engineering standards for prompting, evaluation, observability, and ethical guardrails across WongDoody’s creative technology practice 
• Provision and set up on-premises servers and cloud solutions for usage with GenAI tools 
• Collaborate in cross-functional, agile teams and help evolve WongDoody’s AI-first innovation culture 

What we'd love to see 

• A passion for creative technology, curiosity for emerging AI tools, and the ability to turn ideas into working prototypes  
• Analytical and structured mindset with the ability to make complexity simple 
• End-to-end architecture from prototyping to production (including CI/CD, logging, analytics, and scaling) 
• Strong experience in software engineering (Python and/or TypeScript) 
• Practical knowledge of LLM frameworks,tools and protocols (LangChain, LangGraph, n8n, MCP, A2A, Bedrock, or similar) including agentic architectures 
• Experience in integrating visual AI tools such as ComfyUI, Stable Diffusion, Google Imagen, or Adobe Firefly into broader workflow systems 
• Proven experience integrating text-based AI APIs like ChatGPT, Claude, Gemini, or Llama into end-to-end workflow solutions 
• Familiarity with prompting techniques, RAG pipelines, and AI workflow orchestration including guidance/guardrails, observability (P95, cost/request), evaluation pipelines 
• Understanding of real-time communication protocols (Websocket / gRPC / PubSub event handling) and API integration across data and creative environments 
• Competence in infrastructure setup (Docker, Terraform, cloud platforms like GCP, AWS, or Azure), understanding the resources cost factor and ability to optimize it 
• Open-source engagement or hands-on experimentation with AI agents, visual frameworks, or orchestration systems 
• Excellent English communication skills (German is a plus) 
• Nice to have: Experience with IBM watsonx / Watson AI or related enterprise AI ecosystems  

Your impact 

You’ll shape the future of AI agent experiences, create standards, and transform complex systems into meaningful, measurable experiences - for users, brands, and products. 

We care about your personality and professional skills. We don't care about your gender, age, nationality, or appearance and are open to working with everyone.  

Please note: This is a job ad by WongDoody doo based in Serbia. Through our website or other sources, you may find job ads published by one of our WongDoody sister companies around the globe with whom we act jointly under the band “WongDoody”. For each job offer, only the entity responsible which has published the ad. Contact persons, required information and applicable terms may differ.