ML Engineer Jobs in Lima.
All active ML Engineer roles based in Lima.
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Lead Machine Learning Engineer
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Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end scalable machine learning systems and applications. They use their specialized depth and breadth of knowledge to impact the achievement of client, project or service objectives and advocate for ways of working to promote and deliver excellence. They operate within the framework of functional policies, navigate through intricate challenges and apply their proficiency to contribute to the success of high-stakes projects. Their leadership extends beyond technical prowess, encompassing strategic thinking and effective collaboration to drive innovation and deliver solutions that meet and exceed organizational goals.
As a lead machine learning engineer on projects, you will be leading the design of technical solutions or perhaps overseeing a program inception to build a new system and/or application. Alongside hands-on coding, as a key influencer, you will shape the trajectory of machine learning engineering initiatives, playing a pivotal role in advancing the field and ensuring impactful outcomes for the broader objectives of the company.
Job responsibilities
- You will embrace a strategic mindset, contributing to the direction of machine learning (ML) initiatives and aligning technical solutions with broader organizational goals
- You will play a pivotal role in program inception, shaping the development of new systems and applications from idea to reality, overseeing technical feasibility and resource allocation
- You will leverage your deep understanding of modern architectures to lead the development of scalable and maintainable ML systems, ensuring optimal performance and efficiency
- You will translate client needs into technically feasible and impactful ML applications, driving solution design and deployment within complex, high-stakes projects
- You will own the development and maintenance of ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation
- As a key influencer, you will champion Responsible AI and effective ways of working within the team, advocating for a culture of excellence and continuous improvement
- You will navigate intricate technical challenges with proficiency, employing your specialized knowledge to troubleshoot issues and guide the team towards successful resolutions
- You will stay at the forefront of the evolving field of machine learning, actively seeking out and implementing new technologies and advancements to ensure Thoughtworks remains a leader in innovation
- You will foster a collaborative environment, effectively leading your team through hands-on coding alongside mentorship and guidance, empowering individual growth and knowledge sharing
- You will measure and analyze the impact of ML initiatives, iteratively refining approaches and ensuring solutions deliver tangible value to clients and the organization
Job qualifications
Technical Skills
- You have experience in developing a technical vision and strategy, keeping it relevant and aligned to the business needs
- You can design and execute cross-functional requirements based on business priorities
- You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code using Python or Shell
- You have experience with distributed systems and scalable architectures to handle large-scale ML applications
- You have experience with building, deploying and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch
- You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML
- You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles
- You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
- You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services
Professional Skills
- You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way
- You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives
- You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them
- You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work
- You enjoy influencing others and always advocate for technical excellence while being open to change when needed
- You are a proven leader with a track record of encouraging teammates in their professional development and relationships
- Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business
Other things to know
Learning & Development
There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.
Travel
While we’ve traditionally been a traveling consultancy, we have adopted a hybrid working model with the majority of work being completed remotely from either home or local Thoughtworks offices. However, business travel to client locations should be expected when required by Thoughtworks or our clients’ needs.
Company Policies
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
About Thoughtworks
Thoughtworks is a global technology consultancy that integrates strategy, design and engineering to drive digital innovation. For 30+ years, our clients have trusted our autonomous teams to build solutions that look past the obvious. Here, computer science grads come together with seasoned technologists, self-taught developers, midlife career changers and more to learn from and challenge each other. Career journeys flourish with the strength of our cultivation culture, which has won numerous awards around the world.
Join Thoughtworks and thrive. Together, our extra curiosity, innovation, passion and dedication overcomes ordinary.
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Apply to Referrals OnlySenior Machine Learning Engineer
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Senior Machine Learning Engineers at Thoughtworks build, maintain and test the architecture and infrastructure for managing machine learning applications. They are involved in supporting and contributing to the design of the end-to-end applications and products. They are responsible for building core capabilities including technical and functional machine learning systems and applications, being the anchor for functional streams of work and are accountable for timely delivery.
As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy.
Job responsibilities
- You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
- You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
- You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
- You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
- You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
- You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
- You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
- You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.
Job qualifications
Technical Skills
- An advanced English level is required.
- You must have a strong experience with LLM and AI.
- You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
- You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
- You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
- You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
- You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
- You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
- You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
- You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.
Professional Skills
- You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
- You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
- You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
- You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
- You enjoy influencing others and always advocate for technical excellence while being open to change when needed.
Other things to know
Learning & Development
There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.
About Thoughtworks
Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary.
#LI-Remote
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QA Engineer (AI Assistant Features)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Founding ML Engineer (Spectrum)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Senior AI/ML Engineer (Spectrum)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Security Engineer, Identity and Access Management (IAM)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Senior MLOps Engineer (ML Workflows Engineering)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Senior ML Engineer (JetBrains Research)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Staff Research Engineer (LLM Pre-Training)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Research Engineer (Agentic Models)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
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Senior Machine Learning Engineer (IntelliJ AI)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
Research Engineer (Agentic Behavior – Kotlin AI Value Stream)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains
QA Automation Engineer (IJ Platform / Remote Development)
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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
We are an equal opportunity employer
We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Ready to apply?
Apply to JetBrains