Highlights:

Role: Senior ML-Engineer, Finance

Location: Cyprus, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to own a high-impact client intelligence initiative. Following a successful proof-of-concept with an external consultant, we are bringing this project fully in-house. The ultimate goal is to generate a comprehensive, enriched list of all potential clients globally — understanding their product requirements, industry verticals, and overall revenue potential — and deploy a scoring model that feeds directly into our sales pipeline.

This is an end-to-end ownership role. You will build from the ground up: data collection, enrichment, modeling, and production deployment. The project is co-managed by company executives and has a high strategic value.

What You’ll Do

• Build a market intelligence data-base via collecting different types of data (scraping, enrichment), fixing data pipeline and creating an ML model for scoring and analysis of the raw data.
• Design and operate scrapers to extract key signals from nonprofit websites, including products used, payment tools, and industry vertical indicators.
• Develop critical filters such as an "Is this website for fundraising?" binary classifier, alongside other features that distinguish high-potential prospects.
• Source and integrate financial data from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook.
• Store and structure the enriched dataset in our internal database, making it accessible and useful across the broader team for research and analysis.
• Work closely with the sales team to understand their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion patterns and refine scoring accordingly.
• Deploy the scoring model and own the process of integrating outputs into Salesforce in a clean, maintainable way.
• Build a scraper to monitor existing clients' websites, tracking whether Fundraise Up tools are correctly implemented across their properties.

Challenges You'll Navigate

• At the scale of ~1 million domains, expect domain duplicates, inconsistent data, and significant noise. You'll need to develop robust, cost-efficient filtering pipelines.
• A single model won't cover everything — you'll likely build several targeted sub-models tailored to specific verticals and geographies as the project matures.
• All of this needs to be accomplished without incurring high infrastructure or data costs. Pragmatic, scrappy solutions are valued here.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting) and understanding of modern NLP/LLM approaches
• Proven experience with large-scale web scraping and data pipeline construction
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach; we value clean code, knowledge of design patterns, and solid engineering practices
• Advanced SQL; ability to independently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking and production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down ambiguous problems, choose the right tech stack, and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Infra: linux server admin, distributed computation

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• 31 days off
• 100% paid telemedicine plan
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Role: Senior ML-Engineer

Location: Cyprus, Remote

Language: Russian-speaking team; Strong English required (B2)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to strengthen our ML team. We operate as an internal service and centre of excellence for 10+ product teams at Fundraise Up. This means you won't be tied to a single feature: one day you might be optimising donation amounts and upsell offers, and the next you could be building a smart assistant for the admin panel or working on transaction classification.

We actively use not only classical ML, but also RL, and we're expanding our LLM-based solutions — prompt engineering and pipeline design with LLM APIs (OpenAI and equivalents). That's why we're looking for someone with a broad mindset who isn't afraid to experiment and can choose the most effective approach for each task.

The project's main audience and business team are based in the US. Although the product development team is Russian-speaking, you may occasionally need to write in English.

What You’ll Do

• Develop and deploy ML solutions across different business areas using tabular data (uplift models, recommender systems). We are also actively developing projects that will involve e-commerce mechanics.
• Select the most appropriate ML/LLM approaches or propose alternative solutions.
• Build end-to-end ML solutions: data preparation, training, API development, and monitoring.
• Design prompts and LLM API-based pipelines for specific product tasks: classification, content generation, and response quality evaluation.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting); NLP knowledge is a plus
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (CR, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach to development; we value clean code, knowledge of design patterns, and solid engineering practices
• Data skills: advanced SQL; ability to independently and efficiently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking tools and understanding of production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down problems, choose the right tech stack (or justify a non-ML solution), and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• 31 days off
• 100% paid telemedicine plan
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Join Tenstorrent’s AI Models team and work at the layer most ML engineers never see: bringing advanced models to life on custom AI hardware. You’ll own real workloads end‑to‑end including porting, tuning, and validating LLMs and vision models on our accelerator, and chasing down every last millisecond and percentage point of accuracy. This role is for people who love the craft of ML engineering and want their work to matter at silicon scale, not just behind another API.

This role is hybrid, based in Cyprus.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• Bring up, run, and debug modern ML models (e.g., transformers) using PyTorch or TensorFlow.
• Analyze model behavior and performance, and identify bottlenecks across the stack.
• Improve efficiency, correctness, and scalability of model execution in real systems.
• Work closely with compiler, kernel, and hardware teams to drive performance and system-level improvements.
• Help translate state-of-the-art model architectures into production-grade, high-performance deployments.

What We Need

• Strong experience building and working with ML models in PyTorch or TensorFlow.
• Strong understanding of modern ML model architectures (ex: transformers).
• Solid software engineering fundamentals with strong debugging and problem-solving skills.
• Comfort working in a fast-moving, research-meets-engineering environment.
• Bonus, not required: experience with profiling or performance tuning, or familiarity with quantization, flash attention, kernel fusion, memory hierarchies, C++, CUDA, or systems programming.

What You Will Learn

• How to bring state‑of‑the‑art LLMs and vision models to high performance on a custom AI accelerator.
• How to trace and fix performance bottlenecks from PyTorch code down to kernels and memory systems.
• How to turn research‑grade models into reliable, production deployments on new hardware.
• The practical trade‑offs between techniques like quantization, FlashAttention, and kernel fusion when you’re optimizing real throughput, latency, and memory.
• How your findings can drive changes across compiler, kernel, and hardware teams in a full‑stack co‑design loop

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

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 Assistant is an advanced software tool that leverages artificial intelligence to aid developers in various tasks. Our team develops the AI Assistant plugin for JetBrains IDEs. This tool integrates AI into the coding environment, enhancing features like code completion, debugging, and VCS operations. We’re striving to make JetBrains AI Assistant the most useful and intuitive AI-powered tool on the market, focusing on core features such as code completion, code generation, refactoring, and general assistance via chat.

As part of our team, you will:

• Perform functional, exploratory, and regression testing.
• Design test cases and write specifications.
• Reproduce bugs and verify fixes.
• Communicate with the team, as well as internal and external users.
• Participate in feature discussions and planning.
• Have the opportunity to get hands-on experience working with data, performing online experiments, and measuring the impact of features on end users.

Requirements:

• Experience in testing without functional specifications.
• Knowledge of testing methodologies.
• Understanding of programming concepts sufficient for writing simple applications.
• Experience with Java or Kotlin.
• Commitment to working as a team, sharing your knowledge, and being open to other points of view.

You’ll be great for our team if you:

• Have an interest in machine learning.
• Have experience working with data and know how to make data-informed decisions.

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 

As a Product Manager, you will have sole responsibility over the roadmap of one of our technical products (mapping, marketplace, billing, privacy, etc). You’ll play a pivotal role in shaping its future, working directly with our founder.

What you will be doing

• Lead a cross-functional team of engineers, designers, and data scientists
• Set your team’s goals and roadmap to align with Wheely’s mission
• Own your team’s products (existing and new) across from idea, through development, to launch, growth and maintenance
• Collaborate with other product squads and other stakeholders

Requirements

• 2+ years of proven success working on technical products (platforms, distributed systems, machine learning, mapping, etc.)
• STEM degree or previous experience as an engineer
• Outstanding written communication, with a talent for maintaining accurate feature specifications as the single source of truth
• Highly analytical, with the ability to pull your own numbers and conduct your own analysis

What we offer

• Office-based role in Nicosia, four days a week with flexible start and finish times, plus one remote day of your choice
• Competitive salary
• Employee stock options plan
• Private medical and dental insurance
• Daily Lunch allowance
• Latest-generation MacBook Pro and 4k display 
• Professional development stipend
• Relocation support, including visa sponsorship and allowance

Responsibilities

We are looking for an exceptional Senior Backend Developer (GOlang) to join our growing Engine team. The Engine team develops and maintains most things related to Workato Recipe runtime. Everything related to recipe execution: DSL, pulling events, processing webhooks, executing jobs. There are various aspects to it: performance, scaling, storage, durability, atomicity, concurrency guarantees, data protection, and encryption.

• Build/extend/troubleshot/fix complex heterogeneous GOlang applications, as well as small self-contained GOlang microservices.

• Improve execution engine of custom third-party code (isolation, performance, new features).

• Write well designed, testable, efficient code in GOlang.

• Integration of data storage solutions Postgres/S3/DynamoDB/Kafka/ClickHouse etc.

• Contribute in all phases of the development lifecycle.

• Provide code reviews to your teammates.

• Evaluate and propose improvements to existing system.

• Identify bottlenecks and bugs, and devise solutions to these problems.

• Help maintain code quality, organization and automatization. 

Requirements

Qualifications / Experience / Technical Skills

• Strong experience in building scalable distributed backend applications (7+ years).

• Great understanding of all building blocks of large web applications: databases, load balancers, application servers, message brokers, caching, monitoring, etc.

• Good understanding of network protocols and stacks.

• Good understanding of DB technologies: classic databases and modern no-SQL.

• Knowledge of basic data structures and algorithms and how they are used is a must.

• Excellent debugging, analytical, problem solving, and social skills.

• BS/MS degree in Computer Science, Engineering or a related subject, 7+ years of industry experience.

Can be a plus

• Experience in related fields (DevOps, ML, DBA, Enterprise applications, etc).

• Experience in building/deploying data processing pipelines.

Soft Skills / Personal Characteristics

• Readiness to work remotely with teams distributed across the world and timezones.

Job Req ID: 2314

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

At JetBrains, code is our passion. Since 2000, we’ve focused on helping developers work faster by automating routine checks and fixes.  Our tools are used by over 12.5 million people worldwide, including eighty-eight Fortune Global 100 companies.

We are seeking a detail-oriented IAM Security Specialist to lead the integration, support, and governance of our identity ecosystem. You will be the bridge between technical implementation and security compliance, ensuring that every identity, whether human or machine, has exactly the permissions it needs and nothing more. Your focus will be on building scalable RBAC models and maintaining a rigorous access review cycle.

Key responsibilities

System integration and support:

• Lead the technical integration of new applications and services into our centralized IAM platform.
• Provide expert support for complex authentication/authorization issues and serve as a technical escalation point.
• Maintain and optimize IAM infrastructure, including SSO (SAML, OAuth 2.0, OIDC), MFA, and PAM solutions.

Access governance and permission reviews:

• Execute and oversee periodic access re-certifications, ensuring compliance across periodic audit cycles (SOC 2).
• Conduct detailed permission reviews for individuals and system integrations to enforce the Principle of Least Privilege (PoLP).

RBAC and ABAC modeling:

• Design, document, and implement Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) frameworks across a wide range of systems.
• Partner with cross-functional teams (IT, Product, HR) to define business roles and translate them into technical entitlements.

Required skills and experience

• 3+ years of professional experience focused on Identity and Access Management (IAM) engineering or architecture.
• Proven experience administering enterprise IAM solutions and integrating them with diverse systems (e.g., Okta, Auth0, Ping Identity, Microsoft Entra ID).
• Scripting and automation skills using a scripting language such as Python, Go, Bash, or PowerShell.
• Familiarity with cloud IAM solutions (e.g., AWS IAM, GCP IAM).
• Solid understanding of networking, security protocols, and SSO technologies and standards, including SAML, OAuth 2.0, and OIDC.

Preferred qualifications

• Experience in the software development industry, particularly with managing access to source code repositories (Git/GitHub/GitLab) and CI/CD tools (TeamCity, GitLab CI).
• Hands-on experience with Privileged Access Management (PAM) concepts and tools.
• Knowledge of Zero Trust Architecture (ZTA) principles and how to apply them to developer workflows.
• Security certifications (e.g., CISSP, CISA, relevant vendor certifications).
• Familiarity with compliance frameworks relevant to software vendors (SOC 2).
  
  

Why join JetBrains?

JetBrains provides a highly technical and intellectually stimulating environment. You'll work on identity and access management systems used by millions of developers, with the opportunity to work with cutting-edge technologies every day. Help us keep our tools and systems secure. 
We offer:

• 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 

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 have strived to make the 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 JetBrains Research team explores ways to use machine learning techniques and agentic approaches to help developers and enhance software development processes. Our work aims to improve the state of ML for code by turning the latest academic advances into practical applications.

Our team is looking for an ML Engineer to participate in a variety of projects in areas such as code completion and generation, AI agents development, and test generation. Though we don’t expect the candidate to have experience in all the tasks we work on, we are looking for someone excited to take on the challenge of working in a diverse set of contexts.

In this role, you will: 

• Design and prototype machine learning solutions to improve the software development workflow.
• Apply existing open-source models or train custom ones as needed.
• Build training and evaluation pipelines that support fast iteration and ensure reproducibility.
• Stay up to date with the latest advancements in applying machine learning to source code.
• Collaborate with colleagues and provide mentorship when appropriate.

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

• Have experience designing machine learning systems from scratch.
• Have a background in natural language processing or code modeling.
• Have a proven track record of delivering machine learning projects.
• Know how to design reproducible ML experiments.
• Enjoy working on projects with high uncertainty.
• Are proficient in Python, Java, or Kotlin.
• Have hands-on experience with modern ML frameworks.

It would be nice if you: 

• Have experience applying machine learning to programming languages.
• Have hands-on experience building and improving AI agents.
• Have experience in A/B testing and general knowledge of statistics
• Have worked with large-scale data processing pipelines

#LI-KP1

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 working on an ambitious new platform that provides AI capabilities to all JetBrains products. Our platform is based on models developed in-house for writing and coding assistance, as well as integration with our strategic partners.

We are looking for a Research Engineer who can contribute to training foundation models for coding tasks. You’ll be working on developing Large Language Models from scratch and deploying them into production environments where they will be accessible by end users across the globe.

We value engineers who: 

• Can plan projects and make decisions independently, consulting with others if needed.
• Identify customer needs and prioritize their tasks accordingly.
• Start with the simplest solutions and gradually add complexity as needed.
• Take sole responsibility for an entire subsystem.
• Have a passion for learning and a desire to stay up to date with the latest developments in the LLM field.

In this role, you will: 

• Work with stakeholders to convert business requirements into technical specifications.
• Train LLMs from scratch on a large GPU cluster.
• Collect and process pre-training and fine-tuning datasets.
• Support and improve existing subsystems.

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

• Experience in design, deployment, and support of production ML systems.
• A strong theoretical background in NLP and transformer-based approaches.
• Proficiency with modern deep learning frameworks such as PyTorch and common libraries for NLP.
• Experience in distributed training of multi-billion parameter models.
• Attention to detail in everything you do and great communication skills.

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

• LLM inference frameworks such as vLLM, DeepSpeed, TensorRT.
• LLM alignment techniques such as RLHF/RLAIF.
• MLOps tools and practices, including CI/CD for ML.
• K8s and Kubeflow.
• Scientific publications in the NLP field.

How we develop JetBrains AI: 

• A cluster of hundreds of NVIDIA GPUs as training infrastructure.
• Git for source control management.
• Python, PyTorch, and HuggingFace as an ML stack.
• Kubeflow and Weights & Biases for experiment tracking.
• TeamCity as a CI Automation system.

#LI-KP1

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

At JetBrains, we have a passion for building the strongest, most effective developer tools in the world. Our tools are designed to give developers the freedom to grow, discover, and create. Over eight million of the world's most dynamic developers speed up their workflows using our products, which help them stay focused on code design and the big picture, allowing them to deliver more creative and effective results.

The remote development functionality in JetBrains products redirects IDE-heavy processing from a local machine to a powerful remote server, reimagining how developers work. With hardware performance no longer a limitation, developers can work from anywhere while benefiting from improved security, stability, and reliability.

We're looking for a QA Automation Engineer to join the Remote Development team and help ensure that the products software engineers around the world rely on daily are of the highest quality.

You'll work alongside QA Engineers to design and implement automated testing scenarios that catch issues before they reach our users, cover regressions with automated tests, and improve automation processes within the team.

What you'll do

Core responsibilities

Test automation 

• Design, develop, and maintain automated tests (UI, E2E, functional, and integration) across multiple platforms and environments: Linux, Windows, macOS, Docker, and WSL.
• Expand test coverage for new and existing functionality.
• Monitor automated test execution results.
• Debug and troubleshoot test failures, distinguishing product issues (regressions) from infrastructure-related issues (including test, framework, or environment).
• Optimize test execution time and reliability.
• Improve test automation stability and contribute to automation frameworks.

Quality assurance 

• Report bugs in YouTrack and verify that they are properly fixed and backported. 
• Participate in release quality assessments.
• Collaborate with QA and developers on testability and quality improvements. 
• Help define test strategies and quality gates for your team.
• Support manual QA activities when needed.

Continuous improvement 

• Define and track quality metrics, including testing coverage, failure rate, and flakiness.
• Identify gaps in test coverage and propose solutions.
• Improve domain-specific test infrastructure and CI/CD pipelines within your team's scope.
• Share knowledge about automation best practices with other team members.
• Work with the tooling team to adopt new frameworks and practices.

What we're looking for

Required skills

Technical foundation

• Proven experience in test automation.
• Solid programming skills in Kotlin or Java and a good understanding of the JVM.
• Experience with test frameworks: JUnit or TestNG.
• Understanding of software testing principles and methodologies.
• Familiarity with CI/CD tools (TeamCity or similar).
• Experience with reporting tools (Allure or others).
• Version control experience (Git).

Quality mindset

• The ability to isolate root causes and distinguish product bugs from environment issues.
• Attention to detail while maintaining focus on overall quality goals.

Collaboration

• Excellent communication skills in English, both written and verbal.
• Experience working in cross-functional teams and collaborating with other teams.
• Comfort with giving and receiving constructive feedback.
• The ability to grasp new concepts quickly and to work both in a team and independently.

Nice to have

• Experience testing developer tools, IDEs, and desktop applications.
• Experience building automated testing infrastructure and processes.
• Experience in performance testing.
• Experience in manual testing.

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