A Career with Point72’s Technology Team

As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications.

As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. 

What you’ll do

As a quantitative analyst on our Treasury Analytics team, you will be at the forefront of the firm’s initiative to optimize and improve financing and capital utilization by delivering best-in-class datasets, models, and processes across asset types. The team is highly collaborative and sits within the broader Technology platform. Specifically, you will:

• Develop, implement, and maintain quantitative models for our Treasury team, including models for cash management, liquidity risk, and foreign exchange risk
• Partner with internal teams to impact the firm’s financing capabilities by delivering high-quality calculations, contributing to our Treasury analytics platform, and curating data for wider audiences
• Develop an expertise across our prime brokerage, financing models, and other firm models by engaging with partners and contributing quantitative solutions to a shared repository
• Create and implement solutions that have maximum impact
• Design, socialize, and broaden Treasury’s data platform
• Model and optimize margin across a variety of products
• Build tools to explore complex datasets and identify day-over-day changes, driven by markets movements or changes in firm positioning
• Exchange ideas and best practices with business and technology colleagues
• Own the calculation of key treasury metrics, providing insights, advice, and quantitative leadership where required

What’s required

• Strong academic achievement in a quantitative field with a background in finance or a demonstrated interest in understanding the complexity of financial markets
• Experience contributing to a shared repository, such as Git
• Proficiency in Python and quantitative libraries such as Pandas, PyTorch and NumPy
• Ability to communicate highly complex information in a variety of formats
• Strong work ethic and commitment to carrying solutions from conception to deployment
• Commitment to the highest ethical standards 

We take care of our people

We invest in our people, their careers, their health, and their well-being. When you work here, we provide:

• Sports card
• Private life insurance
• Private medical and dental care, with vision allowance
• Private pension scheme
• Volunteer opportunities
• Support for employee-led affinity groups representing women, people of color and the LGBT+ community
• Business travel accident insurance
• Employee assistance program
• Educational assistance reimbursement

About Point72

Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here

As a C++ Machine Learning Engineer on the AI Models team at Tenstorrent, you’ll work on the training framework behind our most advanced models. You’ll write high-performance C++ code, shape how new layers and operators are implemented, and help models scale across our custom silicon. If you enjoy building the guts of ML systems and seeing them run fast, this role is for you.

This role is hybrid, based out of Warsaw or Gdansk, Poland. We also consider remote candidates on a case-by-case status.

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

• Strong in C++ and low-level systems programming, especially in performance-critical code.
• Comfortable thinking in tensors, memory layout, and compiler graphs.
• Familiar with PyTorch and curious about how frameworks map to hardware.
• A builder who enjoys solving technical puzzles and digging into the details.

What We Need

• Extend and optimize our ML training framework with new ops, layers, and training features.
• Debug and tune model performance on Tenstorrent chips.
• Work with compiler and kernel teams to make sure models compile and run as expected.
• Support integration of real-world models and help bring them into production.

What You Will Learn

• How ML frameworks and compilers connect at the system level.
• How to translate training workloads into low-level operations optimized for custom silicon.
• How large-scale model training works under the hood, from memory layout to operator fusion.
• What it takes to build infrastructure that supports fast iteration in research and production.

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

What You’ll Do:

The GPU Performance Team is responsible for the automated testing and verification of CoreWeave’s ever-expanding fleet of nodes and infrastructure.   The team plays a critical role in ensuring that the hardware we deliver to customers is stable and performant throughout its lifecycle.  

About the role:

We are seeking a Senior Software Engineer to join the GPU Performance team to help us build and refine our automation platforms and workflows for reliability, efficiency, scalability and observability. This individual will join a team of Golang and Python developers innovating kubernetes-based solutions to hardware performance testing. As a member of the GPU Performance  team, you would have the opportunity to:

• Design and Implement solutions for testing infrastructure at scale through automation.
• Develop platforms, workflows, data structures, API endpoints, and other testing management tools and capabilities.
• Create test plans, deployment automation, dashboards, alerts, and insights into our performance testing platform.
• Grow, change, invest in your teammates, be invested-in, share your ideas, listen to others, be curious, have fun, and, above all, be yourself.

Who You Are: 

You are a software engineer with a strong bias toward reliability, automation, and scale. You’re comfortable owning services end‑to‑end and working close to hardware, but your primary tools are Go or Python, Kubernetes, and well‑designed APIs.

• Have experience building and maintaining backend services and APIs (REST/gRPC) and are comfortable integrating with infrastructure systems (Kubernetes, CI/CD, telemetry, metrics backends).
• Are motivated by automation at scale: you’d rather design a controller, workflow, or platform than run one‑off tests by hand.
• Are familiar with system metrics, performance, and health (e.g., GPU/CPU, network, storage, or similar infra) and know how to turn raw metrics into dashboards, alerts, and actionable insights.
• Are comfortable designing and implementing performance tests and validation workflows that run across many nodes and clusters.
• Care about code quality, observability, and operational readiness: logs, metrics, tracing, alerting, and on‑call are part of how you think about building systems.
• Are willing to participate in an on‑call rotation and help own the stability of the platforms you build.
• Work well in a collaborative, curious, and feedback‑driven team: you invest in your teammates, share ideas openly, and are excited to help shape how CoreWeave validates hardware performance at fleet scale.

Preferred:

• Write and maintain Kubernetes custom controllers and operators to automate infrastructure testing.
• Contributions to OSS projects such as  llm-d, vLLM, or PyTorch
• Exposure to benchmarking large GPU fleets or multi-region clusters.
• Experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! 

The base salary range for this role is zł321,000 to zł535,000. The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

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

Location: Poland

We Are:
RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad-buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel.

You Will:
As a Senior Technical Researcher/Engineer within the AdTech Technical Research Team, you'll play a pivotal role in exploring and understanding the latest technologies in the ad tech domain. You'll be responsible for conducting in-depth research, experimenting with new technologies, and collaborating with cross-functional teams to assess their potential for integration into our systems. Your role will involve a blend of programming, research, and analytical skills to evaluate the effectiveness and feasibility of various ad tech solutions.

Desired Experience:

• 5+ years of experience as researcher or engineer.
• Strong technical proficiency: programming skills and the ability to understand large and complex systems and architectures.
• Openness and willingness to experiment & learn: readiness to take on new challenges, explore new technologies, and continuously expand knowledge in the ad tech domain.
• Independence & proactive attitude: ability to take initiative, make decisions, and act without excessive supervision while maintaining a high standard.
• Goal-oriented mindset: focus on achieving specific project goals and adaptability in a dynamic environment.
• Collaboration & communication: ability to cooperate effectively with teammates and other teams, clearly sharing knowledge and cooperating with external organizations (e.g. major browser vendors, W3C, GitHub discussions).
• Ability to build Proof of Concepts (PoCs): creating prototypes and experimental solutions to evaluate effectiveness and utility.
  
  

Selected Technologies & Projects:

• Python, Java, Scala, TypeScript/JavaScript
• PyTorch, NumPy, Pandas
• Jupyter Notebooks
• BigQuery, GCP
• Browser Engines
• Assessing new privacy mechanisms (e.g. Privacy Sandbox APIs) by building PoCs, testing, and suggesting improvements (via GitHub issues or meetings). The goal is to evaluate their feasibility, ensure compliance, and enhance user privacy.
• Exploring solutions for Android and iOS, including creating prototypes to improve performance on mobile platforms. This requires close collaboration with other teams and leveraging ML opportunities.
• Many more — including your own ideas!

We Offer:

• Technology: access to the latest technologies and real opportunity to use of them in a large-scale and highly dynamic projects; extensive and rich datasets
• Impact: your contribution will directly influence the company's business results and outcomes globally, while also giving you the chance to mentor less experienced colleagues in the team
• Wellbeing: extremely flexible conditions – you act when it is convenient for you and devote as much time as you can; you can operate fully remotely
• Culture: be part of a team of enthusiasts with wide experience in ML who willingly share their knowledge and learnings on a daily basis, no BS environment
• Contract Types: B2B

Apply now! 

You don't need to tick every box to apply. If you are passionate about digital marketing, send us your CV, and we'll review it.

Location: Poland

We Are:

RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad-buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel.

Founded in 2012, and now operating in 90+ markets, RTB House has always been private-by-design. It embraces first-party advertising and a relentless approach to innovation. RTB House offers end-to-end Deep Learning-powered AdTech products and solutions to maximize conversion, drive new customer acquisition, create engagement, and fuel long-term demand for a global base of clients.

You Will: 

We're looking for a Senior Software Engineer to help us design, build, and optimize high-performance backend systems that power real-time bidding (RTB) and machine learning at internet scale. You’ll cooperate on software that handles billions of daily transactions with strict latency and reliability constraints - all in a distributed, low-latency environment.

Desired Experience: 

• Expertise in designing and implementing complex IT systems.
• Ability to develop user-friendly, versatile tools.
• Proficiency in at least one programming language, such as Python, C++, Java, or Scala, along with expertise in Linux.
• Strong skills in evaluating and optimizing system performance, from initial design through to production troubleshooting.
• Deep understanding of algorithms and data structures.
• Initiative and creativity to improve existing solutions.
• Ability to cooperate effectively both within and across teams.

Additional Advantages:

• Previous experience in the field of Machine Learning is not required, but would be an asset.
• Solid foundation in mathematics.
• Experience with GPU programming and Machine Learning frameworks such as Torch, PyTorch, or TensorFlow.
• Proven experience with distributed systems.
• Familiarity with Big Data technologies such as Hadoop, Kafka, Storm, Spark, or Flink.
• Hands-on experience with Google Cloud Platform (GCP) or similar cloud providers.

In Return, We Offer:

• A highly competitive salary.
• The opportunity to cooperate with a team of enthusiasts experienced in Machine Learning, Big Data, and distributed systems, who are eager to share their knowledge and skills.
• You can cooperate 100 % remotely or choose one of our office spaces in Warsaw or Cracow.
• Access to the latest technologies, with the opportunity to apply them in a large-scale and fast-paced project.
• An opportunity to apply your expertise in optimizing algorithms that support hundreds of millions of internet users and billions of ad views per month within the RTB model.
• The ability to see the immediate impact of your cooperate on the company's business outcomes.
• The possibility of publishing your results.
• Cooperation based on B2B contract.

Daily Responsibilities:

• Developing and maintaining the ML training platform and the bidding infrastructure that evaluates ML models in the production environment.
• Identifying performance bottlenecks and optimizing critical, low-level parts of the system.
• Ensuring the reliability and scalability of implementations, and creating performance and correctness tests for new system components.
• Testing and benchmarking open-source Big Data and ML technologies to assess their suitability for the production environment.

Apply now!

You don't need to tick every box to apply. If you are passionate about digital marketing, send us your CV, and we'll review it.

Location: Poland

We Are:

RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad-buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel. As an ML Researcher, you will be responsible for its development.

Founded in 2012, and now operating in 90+ markets, RTB House has always been private-by-design. It embraces first-party advertising and a relentless approach to innovation. RTB House offers end-to-end Deep Learning-powered AdTech products and solutions to maximize conversion, drive new customer acquisition, create engagement, and fuel long-term demand for a global base of clients.

You Will:

• Designing and implementing models, most often of deep neural networks, used to predict the behavior and preferences of Internet users
• Analysis of the latest works in the field of Machine Learning
• Conducting and analyzing A/B tests of new solutions
• Developing and testing new approaches to modeling key issues, such as bidding in first-price auctions

Desired Experience:

• 4+ years of hands-on experience with Machine Learning / Data Science 
• Interest and willingness to constantly develop in the area of ​​Machine Learning
• Knowledge of statistics and probability
• Proficiency in programming

Selected technologies used:

• Python, Java, Scala
• PyTorch, NumPy, Pandas
• Jupyter Notebooks

Additional advantages will be:

• Experience in the ML industry
• Experience in designing recommendation systems
• Practical knowledge of the tools we use

Sample topics:

• Implementation and analysis of new model architectures, such as convolutional networks, transformer
• Analyze the difference in the distribution of training and production data. Estimating the scale of the problem, identifying the best solution, analysis, implementation, deployment
• Experiments with the use of transfer learning
• A completely new approach to generating product recommendations that is free from proxy targets and uses contrastive loss function

We Offer:

• Cooperate in a team of enthusiasts with experience in machine learning who willingly share their knowledge and skills
• Extremely flexible cooperation conditions - you cooperate when it is convenient for you and devote as much time as you can; you can cooperate fully remotely
• Access to the latest technologies and the possibility of real use of them in a large-scale and highly dynamic project;
• Possibility of using the possessed knowledge and competences in practical applications - while optimizing algorithms supporting hundreds of millions of Internet users and monthly buyers of billions of advertising views in the RTB model, based on extensive data sets
• The effects of your cooperate immediately visible in the company's business results
• Possibility to publish your results
• Cooperation based on B2B contract or Contract of Mandate 
• You can cooperate 100 % remotely or choose one of our office spaces in Warsaw or Cracow.

Apply now!

You don't need to tick every box to apply. If you are passionate about digital marketing, send us your CV, and we'll review it.

Location: Poland

We Are:

RTB House is a global company that provides state-of-the-art marketing technologies for top brands and agencies worldwide. Its proprietary ad-buying engine is the first in the world to be powered entirely by Deep Learning algorithms, enabling advertisers to generate outstanding results and reach their goals at every stage of the funnel.

Founded in 2012, and now operating in 90+ markets, RTB House has always been private-by-design. It embraces first-party advertising and a relentless approach to innovation. RTB House offers end-to-end Deep Learning-powered AdTech products and solutions to maximize conversion, drive new customer acquisition, create engagement, and fuel long-term demand for a global base of clients.

Desired Experience:

• Expertise in designing and implementing complex IT systems.
• Ability to develop user-friendly, versatile tools.
• Proficiency in at least one programming language, such as Python, C++, Java, or Scala, along with expertise in Linux.
• Strong skills in evaluating and optimizing system performance, from initial design through to production troubleshooting.
• Deep understanding of algorithms and data structures.
• Initiative and creativity to improve existing solutions.
• Ability to work effectively both within and across teams.

Additional Advantages:

• Previous experience in the field of Machine Learning is not required, but would be an asset.
• Solid foundation in mathematics.
• Experience with GPU programming and Machine Learning frameworks such as Torch, PyTorch, or TensorFlow.
• Proven experience with distributed systems.
• Familiarity with Big Data technologies such as Hadoop, Kafka, Storm, Spark, or Flink.
• Hands-on experience with Google Cloud Platform (GCP) or similar cloud providers.

We Offer:

• The opportunity to cooperate with a team of enthusiasts experienced in Machine Learning, Big Data, and distributed systems, who are eager to share their knowledge and skills.
• Flexible cooperate hours, with the possibility of remote cooperate or cooperate from our office in Warsaw.
• Access to the latest technologies, with the opportunity to apply them in a large-scale and fast-paced project.
• An opportunity to apply your expertise in optimizing algorithms that support hundreds of millions of internet users and billions of ad views per month within the RTB model.
• The ability to see the immediate impact of your cooperate on the company's business outcomes.
• The possibility of publishing your results.
• Cooperation based on B2B contract or Contract of Mandate
• You can cooperate 100 % remotely or choose one of our office spaces in Warsaw or Cracow.

Daily Responsibilities:

• Developing and maintaining the ML training platform and the bidding infrastructure that evaluates ML models in the production environment.
• Identifying performance bottlenecks and optimizing critical, low-level parts of the system.
• Ensuring the reliability and scalability of implementations, and creating performance and correctness tests for new system components.
• Testing and benchmarking open-source Big Data and ML technologies to assess their suitability for the production environment.

Apply now!

You don't need to tick every box to apply. If you are passionate about digital marketing, send us your CV, and we'll review it.

About the role:

We're looking for a Principal Data Scientist to own Readdle's company-wide data science roadmap and drive measurable business impact across the organization.

This is a role for a hands-on technical leader with a business mindset — someone who sets methodological standards, prototypes and productionizes predictive and prescriptive systems, and serves as the internal authority on machine learning, autonomous systems, experimentation, causal inference, optimization, and advanced analytics.

You'll work closely with Product, Engineering, Marketing, Data Platform, and Analytics to embed data-driven decision-making into how we build and grow.

What you will do:

• Own the Data Science roadmap and its technical architecture across the company, ensuring focus on the highest-leverage opportunities and scalable foundations.
• Hands-on build and productionize DS models end-to-end: from hypothesis → prototype → reliable production systems that optimize the proper business metrics.
• Methodological excellence: create, maintain, ensure adoption, and evolve advanced analytics frameworks and enablement cross-functionally, including:
• experimentation design and analysis
• causal inference and incrementality testing (incl. diff-in-diff, synthetic control, uplift, geo experiments, incrementality, etc.)
• measurement frameworks and proxy metric design
• optimization & prescriptive analytics
• Inference in marketing measurement (incl. MMM and Bayesian measurement where applicable)
• Develop predictive and prescriptive capabilities, including revenue & churn prediction, time-series forecasting, anomaly detection, and decision-optimization systems.
• Define and defend proxy measurements when direct measurement is infeasible; select the right method for the task and clearly articulate assumptions/tradeoffs.
• Partner with Data Platform & Analytics teams to jointly ensure high-quality, well-modeled, accessible SSOT data for data science;
• Act as the technical bridge between Product, Engineering, and Marketing to ensure data science is embedded in product lifecycle decisions (discovery, rollout, iteration).
• Own & drive standards around DS reproducibility, testing, CI/CD, version control, packaging, documentation, and monitoring.
• Mentor Senior Data Scientists; create learning paths, review work for methodological rigor, and build a culture of technical excellence.

About you:

• Proven experience as a Principal / Staff Data Scientist (or equivalent) delivering cross-functional, company-level impact and setting technical direction.
• Deep expertise in advanced analytics and measurement, including strong proficiency in:
• experimentation and causal inference
• incrementality measurement, optimization / prescriptive analytics
• defining proxy metrics and causal graphs
• Strong track record of building and productionizing ML systems (predictive and/or prescriptive), including:
• time series forecasting and anomaly detection
• causal graphs / structural thinking (when appropriate)
• MMM and/or marketing measurement approaches (as applicable to the business)
• Deep Python expertise plus at least one library in each category:
• ML/DL: (e.g., scikit-learn, XGBoost/LightGBM, PyTorch, TensorFlow)
• Statistics: (e.g., statsmodels, SciPy, etc.)
• Causal inference: (e.g., DoWhy, EconML, CausalML, causalimpact, PyWhy)
• Strong engineering and MLOps fundamentals, including experience with:
• Python in production, containers, and distributed computing
• CI/CD, testing, version control, reproducibility best practices
• modern data modeling frameworks (e.g., dbt/dataform), orchestration patterns, and model monitoring
• AI developer productivity tools and strong craftsmanship
• Excellent business acumen, stakeholder management, and communication: ability to translate complex methods into clear decisions, assumptions, and tradeoffs for senior leaders.
• Ability to operate across ambiguity, prioritize ruthlessly, and deliver outcomes with high standards of rigor.

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'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