We are seeking an experienced Staff Software Engineer / Platform Engineer who will serve as a technical leader with dozens of engineering teams. You are someone who enjoys bridging the gap between software engineering and systems architecture, and not just managing infra, but building Internal Developer Platform (IDP) on Kubernetes, and APIs that enable scalability, efficiency, productivity, and developer joy. You are a "doer" who can pivot from writing high-quality production code to influencing the architectural direction of our CI/CD pipelines and service catalogs (e.g., Backstage), as well as be the next frontier of Generative AI integration.

Our Developer Experience (DevEx) organization’s mission is to partner with SentinelOne engineering teams to accelerate the velocity of software delivery through continuous innovation and standardization. We are building a platform that serves nearly 1,000 engineers to release services and features to our customers, making it easy to move from POC to production safely and quickly. We're also transforming our CI/CD from a traditional pipeline into an AI-driven engine - you will help us build a platform where AI proactively helps developers write & ship code, generates high-coverage test suites on the fly, and performs the first pass of PR reviews with human-level context. 

What Will You Do?

• Partner with Engineers, Build & Automate: The engineering teams are our primary customers - you will be working with them to understand their pain points and find long term solutions.
  • You will be building the IDP as the "Golden Path", and tools that improve the quality of life and streamlining the development process for the teams, so that they can build without having to worry about the underlying infrastructure.
  • You will be also building scalable solutions in collaboration with other infrastructure teams.
• Modernize the Stack: Collaborate with architects to evaluate and implement modern tools (e.g., ArgoCD, GitHub Actions) and deployment strategies (Canary, Blue/Green).
• Lead the AI-Driven CI/CD Shift: Architect and implement AI-powered workflows that assist in code generation, automated testing, and intelligent PR analysis to eliminate developer friction.
• Operational Ownership: Identify causes of toil across engineering orgs and eliminate them through automation, enhancing overall system reliability and developer satisfaction.
• Cross-Functional Influence: Partner with Product, Security, and Finance teams to align technical roadmaps with business value and customer needs. You will influence strategy and ensure our platform is as lean as it is powerful.
• Impact: You will participate in the full software development lifecycle, including requirements analysis, architecture design, coding, testing, and deployment.
• Deal with global scale: Our security SW products protect 15,000 enterprise and government clients across the globe, incl. 4 of Fortune 10, and process 9+ Petabytes of data daily and 3+ Trillion security events across multiple AWS/GCP regions and GovCloud, supported by a large Kubernetes control plane with 80+clusters and tens of thousands of nodes.

Our stack: Go, Python; Kubernetes, Docker, AWS, GCP, FedRAMP; GitHub Actions, ArgoCD; GitHub Enterprise; depending on the requirements of the service for communication, we use Kafka, REST API, GraphQL, gRPC, etc.; Postgres, MongoDB, Redis, ClickHouse; Prometheus/Thanos, Grafana

What Skills and Knowledge Will You Bring?

• Demonstrated proficiency in Go or Python. Experience in the full SDLC, from requirements to production-ready code
• Experience with AWS and/or GCP. Knowledge of Kubernetes or similar orchestration systems
• Experience with CI/CD tooling at scale (e.g., GitHub Actions, ArgoCD, Jenkins etc.) and GitOps approach
• Strong experience with Terraform, Pulumi, or similar IaC frameworks
• Familiarity with DevEx fundamentals, including Service Catalogs (Backstage), REST APIs, or gRPC
• Familiarity with both SQL (Postgres) and NoSQL (MongoDB, ClickHouse, or Redis)
• You are passionate about (and ideally have experience in) integrating LLMs and AI agents into the developer workflow to drive productivity
• Excellent problem-solving skills, strong ownership and accountability, with proven experience driving large, impactful projects
• Strong communication skills and ability to articulate technical concepts and influence engineering direction across teams, departments, and stakeholders in multiple time zones

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

Be part of an inclusive, innovative workplace that values belonging, flexibility, and growth!

As a Senior Windows Identity Detection Engineer you will research and detect emerging identity threats by developing behavior-based detection methods. You’ll build tools and PoCs to identify and prevent attacks such as Pass-the-Hash, Silver Ticket, and MFA bypass. Your work will directly strengthen the security of millions of Windows endpoints protected by the platform. In this role, you’ll have a unique opportunity to expand your skillset beyond just Windows security, and to not only contribute, but to significantly influence the buildout of a new side of our business - Identity security - from the ground up!

What will you do?

Primary responsibilities include: 

• You’ll be responsible for detecting the newest identity threats. Your role won’t end with a hypothesis or a document - you’ll have an end to end responsibility for behaviour based detection capabilities, starting from researching attack techniques, designing new methods to detect or prevent those, and implementing it in the product in the end (SW development in C++23 and scripting in Lua).
• You’ll be developing and using internal research tools, PoCs and discovering new ways to detect/prevent identity-based attacks (Pass the Hash, Silver ticket, MFA bypass and more). 
• At the end of the day, your deliveries will enhance the security of dozens of millions of Windows endpoints which are protected by our platform.

What experience or knowledge should you bring?

Ideal candidates will have: 

• 3+ years of experience in malware analysis (statically and dynamically)
• 3+ years of experience with C++, an advantage would be knowledge of Lua or similar scripting language 
• Excellent understanding of the Windows Internals  - understanding how core system components (Process and Threads, Virtual Memory and more) work behind the scenes.
• Experienced with analysis tools, such as: IDA, WinDBG, SysInternals etc.
• A big plus - experience with Identity-based attacks (Pass the Hash, Silver ticket, MFA bypass and more)
• An advantage would be - kernel development experience and/or understanding of existing AVs internals

Why SentinelOne? 

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

Be part of an inclusive, innovative workplace that values belonging, flexibility, and growth!

As a Senior ML Engineer you will join our Static AI team which develops state-of-the-art ML models that operate on millions of machines worldwide, making sub-second decisions to stop malware before it runs. We bring together cross-functional skill sets, including data science, ML engineering, and software engineering, to research, develop, ship, and support ML malware detection engines across Windows, Mac, and Linux machines and cloud environments.

What Will You Do?

Primary responsibilities include: 

• Data pipeline architecture: Design, build, and maintain scalable data pipelines to handle millions of data points from internal and external sources
• ML infrastructure: Develop and optimize the infrastructure required for training, evaluating, and deploying ML models at scale
• Cross-functional Collaboration: Work closely with Data Scientists and Software Engineers to translate research into production-ready detection engines
• System optimization: Build and improve analytics systems that learn from a wide variety of data sources to enhance our existing ML models
• Production support: Ensure the reliability and performance of ML malware detection engines across Windows, Mac, Linux, and cloud environments
• "Production experience" - good level of coding, tests, dealing with CI
• You will also be encouraged to write white papers, blogs, and articles or present in meetups / conferences (but only if you wish to)

What Skills and Knowledge Will You Bring?

Ideal candidates will have: 

• Degree in Computer Science or Mathematics, or equivalent experience
• Experience with collecting and building large datasets for training machine learning models
• Producing, deploying and running ML in production environments
• Experience working with Big data technologies, such as Spark/Databricks, Hadoop, and others 
• Ability to work collaboratively to translate business requirements into technical solutions
• Willingness and ability to work in a diverse, globally distributed team
• The ability to work on difficult problems independently
• Strong communication skills. Our team relies on strong communication, since we have a diverse and sometimes exclusive set of skills, yet our end product relies on all team members. Thus, we need our team members to be able to communicate with people outside our team (with a wide range of backgrounds/positions, product/support/engineering, …)
• A fiery determination and a strong team-player mindset - the team's defining trait is an 'all hands on deck' attitude

Experience in some of these areas is an advantage

• Experience in the cyber domain - security products, especially detection systems
• Cloud infrastructure (AWS) / MLOps experience
• Experience working with Infrastructure as code (IaC)
• AI tooling experience - We are an AI-oriented engineering team. We believe in automating the mundane so our developers can focus on high-level architecture and complex problem-solving. We provide the latest enterprise AI tools and encourage a culture of 'working smarter, not harder.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

As a Senior Software Engineer - Agent (Endpoint Protection) Platform, you will design, develop, and operate large-scale, low-latency applications engineered to process several millions of events per second. You will own the end-to-end lifecycle of high-volume data pipelines, ensuring mission-critical stability and data integrity through rigorous testing and proactive monitoring of key performance metrics. By continuously refining the codebase and optimizing for distributed scale, you will build the resilient backbone that allows SentinelOne’s platform to stay ahead of global cyber threats in real-time.

What will you do?

• Design, develop, implement, test, document, and operate large-scale, high-volume and low latency applications, built to handle several millions of events per second.

• Translate business and functional requirements into robust, scalable, operable solutions that work well within the overall data architecture.

• Participate and collaborate with cross functional teams in the organization to understand the business requirements and to deliver solutions that can scale.

• Maintain application stability and data integrity by monitoring key metrics and improving codebase accordingly.

• Understand & maintain existing codebase by regular re-factoring and applying requested fixes and features.

• Learn new technologies that can solve our huge volume of data and the challenges it poses.

Your Toolkit:

• Our new components are primarily developed in Go and Java, and we use Python in our current backend environment.

• Communication between microservices is facilitated using gRPC, REST, GraphQL APIs, and Kafka, depending on specific requirements.

• We use Redis, PostgreSQL, Cassandra, ClickHouse and have our columnar time-series database for efficient event storage and retrieval at scale.

• Our services are deployed across multiple AWS/GCP regions with Kubernetes; among other tools, you'd also use Docker, GitHub and ArgoCD.

• To enable you in your work, we provide company access to various modern AI-powered tools for both R&D and non-R&D tasks.

What Skills and Knowledge Will You Bring?

• Multiple years of professional backend development experience in one or more of the following: Golang, Java, Python

• Ability to quickly dive into new products and understand their inner workings

• Self-driven individual

• Experience with large-scale high-load distributed systems & performance

• Experience with AWS, GCP, and/or other cloud platforms, and with Docker, Helm, and Kubernetes

• Excellent communication skills - you will be regularly in touch with Product, Technical Account Managers (who provide feedback from clients) and other cross-functional teams

• Experience with Kafka, PostgreSQL, MongoDB, Redis

• Experience in an enterprise SaaS company or cybersecurity SaaS company

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.

• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.

• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.

• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.

• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.

• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

As a Staff (techlead-level) Infrastructure Engineer, you will lead the design, implementation, and evolution of our cloud infrastructure platforms that power SentinelOne’s products at scale. You will drive complex, cross‑functional initiatives end‑to‑end, set technical direction for Kubernetes and cloud infrastructure (70+ K8s clusters, tens of thousands of nodes, multi‑region AWS (EKS) and GCP (GKE), multi‑account setup), and raise the bar for reliability, performance, and security. You will act as a go‑to expert and mentor for other engineers, helping them develop, deliver, and operate services efficiently on top of our platform.

What Will You Do?

Primary responsibilities include: 

• Own, design, build, and evolve systems and large, impactful initiatives (complex, ambiguous problems) across Kubernetes and cloud infrastructure that allow our engineers to deliver features safely, quickly, and reliably – such as the cloud infrastructure platform we’re building.
• Maintain and enhance large‑scale Kubernetes infrastructure, troubleshoot and resolve complex issues in the platform and related cloud services, including performance, scalability, and reliability, as well as H-A, observability, security, and cost-efficiency challenges.
• Ensure our Kubernetes infra and surrounding ecosystem are fully automated using IaC (Terraform, incl. writing, maintaining and improving modules & tooling) and GitOps (ArgoCD) and adhere to best practices in security and compliance. You will also define & evolve standards and patterns across teams and guide others in adopting these practices.
• Support Engineering teams as a trusted partner, helping them adopt and utilize the platform effectively (repeatable, self‑service infrastructure), and influence roadmaps with infrastructure & reliability considerations.
• Own and continuously improve key metrics around performance, throughput, reliability, and failure rates, including capacity planning and deployment strategies.
• Contribute to and sometimes lead incident response efforts, post‑incident reviews, and systemic improvements to prevent recurrence.
• As Staff Engineer, you will be expected to mentor and coach other engineers, fostering a culture of knowledge sharing, continuous learning, and high‑quality engineering practices.

What Skills and Knowledge Will You Bring?

Ideal candidates will have:

• Multiple years of hands-on Kubernetes administrator experience, including maintenance, configuration, and operations in large-scale production environments - such as dozens of clusters, hundreds of nodes, multi‑region, or multi‑account setups.
• Experience with managed offerings like EKS and/or GKE. KOPS and others are a plus.
• Strong experience with ingress controllers configuration and troubleshooting (like Traefik or Gloo) and production experience maintaining standard add-ons (like cert‑manager, Karpenter, Keda, Cilium, CoreDNS etc).
• Deep, practical experience with GitOps tooling and workflows, ideally ArgoCD and/or Flux; with CI/CD pipelines, ideally GitHub Actions, including designing and operating workflows for infrastructure and application delivery.
• Strong experience with Terraform or Terragrunt, including designing and maintaining reusable modules and shared infrastructure components.
• Ability to design automation and tooling to streamline day-to-day operations such as cluster lifecycle, upgrades, and policy enforcement. 
• Highly preferred: proficiency in Python or Golang, with the ability to automate operations, build small tools or services, and review code for quality and reliability.
• Strong AWS and/or GCP infrastructure knowledge across core services, networking, security, IAM, and cost optimization.
• Solid understanding of SRE principles, including SLAs, SLOs, and SLIs, and how to design systems to meet them.
• Incident response experience, including participation in on‑call rotations and leading or contributing to incident reviews.
• Experience leading technical projects from start to finish - you will take full ownership of  work, catch issues early and create solutions that help different teams and services work better together. Strong ability to handle context-switching.
• Experience mentoring and coaching engineers, driving improvements in engineering practices, and fostering a collaborative, learning‑oriented environment.
• Experience using AI tools in day-to-day engineering work and a solid understanding of FinOps practices for managing and optimizing cloud costs.

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

We are seeking an experienced Staff Platform Engineer / Software Engineer who will serve as a technical leader with dozens of engineering teams. You are someone who enjoys bridging the gap between software engineering and systems architecture, and not just managing infra, but building Internal Developer Platform (IDP) on Kubernetes, and APIs that enable scalability, efficiency, productivity, and developer joy. You are a "doer" who can pivot from writing high-quality production code to influencing the architectural direction of our CI/CD pipelines and service catalogs (e.g., Backstage), as well as be the next frontier of Generative AI integration.

Our Developer Experience (DevEx) organization’s mission is to partner with SentinelOne engineering teams to accelerate the velocity of software delivery through continuous innovation and standardization. We are building a platform that serves nearly 1,000 engineers to release services and features to our customers, making it easy to move from POC to production safely and quickly. We're also transforming our CI/CD from a traditional pipeline into an AI-driven engine - you will help us build a platform where AI proactively helps developers write & ship code, generates high-coverage test suites on the fly, and performs the first pass of PR reviews with human-level context. 

What Will You Do?

• Partner with Engineers, Build & Automate: The engineering teams are our primary customers - you will be working with them to understand their pain points and find long term solutions.
  • You will be building the IDP as the "Golden Path", and tools that improve the quality of life and streamlining the development process for the teams, so that they can build without having to worry about the underlying infrastructure.
  • You will be also building scalable solutions in collaboration with other infrastructure teams.
• Modernize the Stack: Collaborate with architects to evaluate and implement modern tools (e.g., ArgoCD, GitHub Actions) and deployment strategies (Canary, Blue/Green).
• Lead the AI-Driven CI/CD Shift: Architect and implement AI-powered workflows that assist in code generation, automated testing, and intelligent PR analysis to eliminate developer friction.
• Operational Ownership: Identify causes of toil across engineering orgs and eliminate them through automation, enhancing overall system reliability and developer satisfaction.
• Cross-Functional Influence: Partner with Product, Security, and Finance teams to align technical roadmaps with business value and customer needs. You will influence strategy and ensure our platform is as lean as it is powerful.
• Impact: You will participate in the full software development lifecycle, including requirements analysis, architecture design, coding, testing, and deployment.
• Deal with global scale: Our security SW products protect 15,000 enterprise and government clients across the globe, incl. 4 of Fortune 10, and process 9+ Petabytes of data daily and 3+ Trillion security events across multiple AWS/GCP regions and GovCloud, supported by a large Kubernetes control plane with 80+clusters and tens of thousands of nodes.

Our stack: Go, Python; Kubernetes, Docker, AWS, GCP, FedRAMP; GitHub Actions, ArgoCD; GitHub Enterprise; depending on the requirements of the service for communication, we use Kafka, REST API, GraphQL, gRPC, etc.; Postgres, MongoDB, Redis, ClickHouse; Prometheus/Thanos, Grafana

What Skills and Knowledge Will You Bring?

• Demonstrated proficiency in Go or Python. Experience in the full SDLC, from requirements to production-ready code
• Experience with AWS and/or GCP. Knowledge of Kubernetes or similar orchestration systems
• Experience with CI/CD tooling at scale (e.g., GitHub Actions, ArgoCD, Jenkins etc.) and GitOps approach
• Strong experience with Terraform, Pulumi, or similar IaC frameworks
• Familiarity with DevEx fundamentals, including Service Catalogs (Backstage), REST APIs, or gRPC
• Familiarity with both SQL (Postgres) and NoSQL (MongoDB, ClickHouse, or Redis)
• You are passionate about (and ideally have experience in) integrating LLMs and AI agents into the developer workflow to drive productivity
• Excellent problem-solving skills, strong ownership and accountability, with proven experience driving large, impactful projects
• Strong communication skills and ability to articulate technical concepts and influence engineering direction across teams, departments, and stakeholders in multiple time zones

Why SentinelOne?

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

Be part of an inclusive, innovative workplace that values belonging, flexibility, and growth!

As a Senior Data Engineer, you will play a vital role in designing, building, and maintaining the data infrastructure that powers our cyber threat detection research. This infrastructure will enable data scientists and security researchers to make sense of petabytes of data and uncover the threats that matter. You will collaborate closely with cross-functional teams across the company — data scientists, security researchers, product managers, and engineers — to deliver innovative data solutions that help us build best-in-class threat detection and protect our customers.

What will you do?

Primary responsibilities include:

• Design, build, and maintain scalable data pipelines that process petabytes of security data.
• Develop production-grade pipelines, applying software engineering best practices.
• Operate big data infrastructure and cloud data warehouses with a focus on reliability and performance.
• Partner with data scientists and security researchers to deliver impactful data solutions.
• Ensure data quality, observability, and governance across the platform.

Ideal candidates will have:

• 4+ years of experience in data engineering, data architecture, and distributed systems
• Proficiency in programming languages such as Python (that we use), Java, Scala, or similar.
• Experience with cloud-based technologies such as AWS (our primary), GCP or Azure.
• Experience with deploying big data technologies such as Apache Spark, Hadoop, Hive, IceBerg, Trino.
• Familiarity with data warehousing concepts and technologies.
• Experience with data visualization tools such as Tableau, PowerBI, Grafana or similar.
• Strong problem-solving skills, with the ability to develop innovative solutions to complex problems.
• Excellent communication skills, with the ability to clearly present and explain complex data and models to technical and non-technical stakeholders.
• BS or higher degree in Computer Science, Statistics, Mathematics, or related field. Additional or directly relevant experience will be considered in lieu of a degree.
• Experience in leading cross-functional projects between R&D and product teams.

Why SentinelOne? 

AI is redefining how the world operates and rewriting the rules of security in real time, and SentinelOne was built for this moment. From day one, we architected an AI-native platform designed to operate at machine speed, not as an add-on to legacy systems but as the foundation itself. If you want to build where innovation and impact move together, this is that place.

We invest in our Sentinels with comprehensive, competitive benefits designed to support you and your family:

• Enjoy flexible hybrid work in Prague (Karlin), Brno (Clubco), or remotely across CZ/SK. Only Prague-based employees are required to work from the office at least two days per week.
• Stock & Bonuses: Grant of Restricted Stock Units with a 4-year vesting plan, annual performance-based bonuses, and an employee stock purchase plan.
• Time Off & Well-being: Flexible Time Off, on top of the standard 5 weeks vacation, flexible paid sick days, fully paid Short Term Sick/Nursing Leave, 16-week parental leave, grandparent leave, and additional company holidays.
• Insurance & Health: Pension Insurance Contribution, Premium life insurance, Private medical care (for you and +1), and a Global Employee Assistance Program.
• Work Perks: Monthly meal and well-being allowance, high-end MacBook/Windows laptop, work-from-home support, and in-office refreshments.
• Growth & Community: LinkedIn Learning, internal mentoring, educational support, generous referral bonuses, and optional company events (sports, BBQs, charity).

Be part of an inclusive, innovative workplace that values belonging, flexibility, and growth!

• Optimize I/O for emulated disk and network devices
• Integrate the hypervisor with other platform services and storage facilities for user data
• Efficiently distribute resources between virtual machines
• Improve guest system support
• Advance the cutting-edge of open source virtualization
• Provide low-level security for the hypervisor and emulator
• Provide general support, fix bugs, and monitor the upstream
• Collaborate with other team members and stakeholders

• 5+ years of professional software engineering experience
• Fluent in C programming language
• 3+years of experience with Linux
• At least 3 years of engineering experience with QEMU/KVM
• General understanding of x86-compatible systems (virtual memory, interrupts, privilege rings)
• Experience writing general system code in user mode for Linux, including debugging, analysis, and optimization tools (the emulator is built on the user mode system process for Linux)

• Aсcepted patches in Linux Kernel or QEMU/KVM
• Experience working with Linux kernel
• Some experience with ARMv8, including virtualization extensions
• Understanding of PCI, SCSI, and ACPI
• Experience working with the Linux kernel
• Excellent communication skills for cross-team collaboration
• Strong work ethic

We conduct coding interviews as part of the process.

THE ROLE

Our Senior Applied AI Engineer builds and operate production-grade AI systems that extract meaning from large-scale unstructured document collections, enabling enterprise data discovery classification, and governance. 

This role owns the full lifecycle of graph intelligence solutions — from problem definition and data modelling, to building and enriching knowledge graphs, and deploying ML- and LLM-assisted analytics in production. The focus is on semantic and contextual analysis of unstructured data to uncover relationships, patterns, and insights that support AI safety, security, and compliance requirements.

WHAT YOU'LL DO

• Design, build, and deploy graph-based AI solutions, combining knowledge graphs, LLMs, and ML models applied to large-scale unstructured data
• Define and own data pipelines that extract, transform, and enrich entity relationships into production-grade knowledge graphs
• Integrate LLMs and ML models into text processing pipelines for classification, embedding generation, document similarity, and semantic analysis 
• Design, deploy, and operate graph and vector databases to support retrieval, reasoning, and analytics
• Optimize models and inference pipelines for production constraints including latency, throughput, cost, and infrastructure
• Deploy, monitor, and iterate on ML systems in production environments ensuring reliability and continuous integration
• Drive architectural decisions and technical direction for applied AI and graph intelligence solutions
• We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• Proven experience in developing and deploying to production knowledge graphs in a real business scenario
• Strong hands-on background in developing text-based ML and LLM systems, including prompt context engineering, optimized for production environments
• Strong proficiency in Python, ML / KG frameworks and tools (e.g. Neo4j, NetworkX, Node2Vec, SentenceTransformers) with the ability to select the right tool for the problem at hand
• Ability to apply the appropriate graph algorithms and design choices for problem solving, including relationship and ontology modelling, feature definition, supervised vs unsupervised graph analytics
• Ability to design clean, modular, and testable ML code in a collaborative environment
• Experience with MLOps practices, building production-grade Docker images, and development of AI solutions designed for integration into production systems
• Experience collaborating with software engineers, product managers, and business stakeholders
• Strong communication skills and ability to explain ML concepts and system behavior clearly

 #LI-ONSITE

THE ROLE

Join the Infrastructure and Shared Services (ISS) team as a Security Engineer to build and defend the next generation of the Everpure Platform. Whether your expertise lies in network architecture, detection engineering, or securing AI pipelines, you will play a critical role in protecting our engineering infrastructure from lateral movement and advanced threats. You’ll collaborate directly with Platform Reliability and Infrastructure teams to bake security into the automation that powers our global developer services. This is a high-impact, hands-on engineering role focused on creating a resilient, zero-trust environment for our most critical services.

WHAT YOU'LL DO

• Engineer Advanced Defense Patterns: Design and implement zero-trust network access models, secure service-to-service communication, or AI-specific guardrails to eliminate unauthorized data access and lateral movement.
• Operationalize Detection & Response: Build high-fidelity behavioral detections for infrastructure and identity systems, ensuring all security telemetry is integrated into our SIEM for real-time visibility and rapid incident containment.
• Validate & Harden Infrastructure: Conduct threat modeling and security validation exercises (including ransomware simulations) to verify the effectiveness of controls across Kubernetes, cloud-native workloads, and AI model pipelines.
• Automate Security at Scale: Partner with engineering teams to integrate security controls directly into infrastructure-as-code and CI/CD pipelines, automating log analysis and network policy enforcement to reduce manual overhead.

WHAT YOU BRING

• Advanced knowledge of securing distributed systems, with deep technical proficiency in either network protocols (TCP/IP, TLS/SSL), detection engineering methodologies, or AI/ML pipeline security (protecting against prompt injection and data leakage).
• Hands-on experience securing cloud-native environments (AWS/Azure/GCP), containerized workloads (Kubernetes), and modern infrastructure-as-code automation.
• Ability to distinguish legitimate operational activities from indicators of compromise through deep log analysis, packet inspection (Wireshark), or behavioral modeling in SIEM/XDR platforms.
• Proven track record of working alongside DevOps, SOC, and Data teams to drive security outcomes without compromising engineering velocity.
• We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Everpure’s policies, unless you are on PTO, or work travel, or other approved leave.

  #LI-ONSITE

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 

The role

This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include:

• investigating how test-time guided search can be used to build more powerful agents;
• dramatically scaling task data collection to power reinforcement learning for SWE agents;
• maximizing efficiency of LLM training on agentic trajectories.

One example of an AI product that we are deeply involved in is Nebius Token Factory — an inference and fine-tuning platform for AI models.

This role will require expertise in distributed systems to build large-scale LLM training platform.

Your responsibilities will include: 

• Designing and developing LLM training platform.
• Maintaining our ML infrastructure, ensuring optimal performance, scalability and reliability.
• Improving job scheduling strategies to minimize resource fragmentation. 

We expect you to have:

• 5+ years of professional software development experience.
• Strong software engineering skills (we mostly use Python and Go).
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing.
• Experience with developing web services.
• A commitment to maintaining extreme rigor in all job-related activities.

Nice to have:

• Previous experience working with language models or other similar NLP technologies.
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess.

The role

Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale.

• Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency.

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation.                                                                                
• Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and reinforcement learning.

• Deep expertise in modern deep learning for language processing and generation

• Experience with training large models on multiple computational nodes

• Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)

• Strong software engineering skills (we mostly use Python)

• Deep experience with modern deep learning frameworks (we use JAX)

• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing

• Strong communication and leadership abilities

Nice to have:

• Previous experience working with language models or other similar NLP technologies.

• Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization

• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.

• Strong engineering skills, including experience in developing large distributed systems or high-load web services.

• Open-source projects that showcase your engineering prowess

• Excellent command of the English language, alongside superior writing, articulation, and communication skills.

Token Factory is a part of  Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens.

In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets.

Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about.

If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story.

The Role

Your responsibilities will include:

• Ensure fault-tolerance, scale, and uninterrupted operations for the service.
• Use cutting-edge cloud technology to solve a variety of infrastructure problems.
• Implement and improve CI/CD processes.

We expect you to have:

• Solid experience with programming languages (like Go, Python, or C++);
• Solid understanding of classic algorithms and data structures;
• Commercial experience with and deep understanding of Unix systems and network technology;
• Experience with systems for containerization and configuration management (Ansible, Salt, Terraform, Docker, K8s, Helm).

It will be an added bonus if you have:

• Desire to be involved in backend development;
• Experience designing, developing, and running high-load distributed systems;
• Commercial experience with a variety of cloud platforms.

We conduct coding interviews as part of the process.

The Role

Your responsibilities will include:

• Ensure fault-tolerance, scale, and uninterrupted operations for the service.
• Use cutting-edge cloud technology to solve a variety of infrastructure problems.
• Implement and improve CI/CD processes.

We expect you to have:

• Solid experience with programming languages (like Go, Python, or C++);
• Solid understanding of classic algorithms and data structures;
• Commercial experience with and deep understanding of Unix systems and network technology;
• Experience with systems for containerization and configuration management (Ansible, Salt, Terraform, Docker, K8s, Helm).

It will be an added bonus if you have:

• Desire to be involved in backend development;
• Experience designing, developing, and running high-load distributed systems;
• Commercial experience with a variety of cloud platforms.

We conduct coding interviews as part of the process.

• Ensure reliability, availability and performance of compute nodes running VMs
• Analyze and debug Linux systems across user space and kernel space, understanding capabilities, limitations and trade-offs at each layer
• Troubleshoot complex production issues involving CPU, memory, NUMA, cgroups and scheduling
• Work hands-on with virtualization and containerization, primarily using QEMU/KVM and Linux-native technologies
• Design and evolve observability as a core capability of the node layer: metrics, logs, traces, alerts, SLIs and SLOs
• Lead incident response, root-cause analysis, and postmortems, driving long-term reliability improvements
• Collaborate closely with platform, kernel/hypervisor, GPU and infrastructure teams to improve system design and operability

• Experience with Kubernetes internals or node-level components
• Hands-on experience with low-level Linux debugging tools (e.g. perf, eBPF, ftrace, strace, kernel crash dumps)
• Familiarity with large-scale compute or bare-metal platforms
• Contributions to open-source infrastructure or system software
• Experience debugging hardware and driver-level issues, including GPUs, NVLink, InfiniBand

The Role

Your responsibilities will include:

• Ensure fault-tolerance, scale, and uninterrupted operations for the service.
• Use cutting-edge cloud technology to solve a variety of infrastructure problems.
• Implement and improve CI/CD processes.

We expect you to have:

• Solid experience with programming languages (like Go, Python, or C++);
• Solid understanding of classic algorithms and data structures;
• Commercial experience with and deep understanding of Unix systems and network technology;
• Experience with systems for containerization and configuration management (Ansible, Salt, Terraform, Docker, K8s, Helm).

It will be an added bonus if you have:

• Desire to be involved in backend development;
• Experience designing, developing, and running high-load distributed systems;
• Commercial experience with a variety of cloud platforms.

We conduct coding interviews as part of the process.

The role

At Nebius, we’re building a next-generation AI compute platform for large-scale ML training and inference — from a few nodes to thousands of GPUs.
We’re looking for a Technical Product Manager to own product direction for Soperator — our Slurm-on-Kubernetes control plane for GPU clusters.
In this role, you will shape how ML engineers and research teams run, scale, and optimize distributed workloads in production.
If you care about systems that combine performance, reliability, and developer experience at the frontier of AI infrastructure, this role is for you.

Your responsibilities will include: 

• Own the full user journey across Soperator clusters: Slurm workflows, dashboards, alerts/notifications, node lifecycle, and training/inference capacity management.
• Define product direction end-to-end: problem discovery → solution design → delivery → adoption.
• Lead deep customer discovery through interviews, usage analytics, and workload analysis to uncover high-impact opportunities.
• Drive execution across platform teams: compute, networking, storage, observability, IAM and etc.
• Translate frontier ML and infrastructure ideas into practical product capabilities for real-world GPU clusters.
• Define success metrics, prioritize roadmap decisions with data, and ensure measurable customer/business impact.
• Lead the open-source strategy and execution for Soperator: shape public roadmap themes, prioritize OSS-facing capabilities, and ensure strong adoption in the community.  

We expect you to have: 

• 3–5+ years in Product Management, ML infrastructure/MLOps, distributed systems, or cloud platform engineering.
• Strong technical depth in distributed systems, cloud infrastructure, or ML platforms.
• Hands-on familiarity with large-scale ML training and orchestration tools (e.g., Slurm, Kubernetes, Ray).
• Track record of shipping technically complex products with multiple engineering teams.
• Strong communication and stakeholder management across engineering, research, and customers.
• Experience with product analytics, data-informed prioritization, and experimentation.
• High ownership, high learning velocity, and comfort operating in fast-moving AI infrastructure environments.

It will be an added bonus if you have: 

• Experience with GPU platforms and HPC primitives: InfiniBand/RDMA, topology-aware scheduling, high-throughput storage.
• Practical understanding of modern ML training stacks: PyTorch, DeepSpeed, FSDP/ZeRO, NCCL.
• Familiarity with efficiency and reliability metrics: Goodput, MFU, failure modes, preemption handling, health checks.
• Exposure to large-scale LLM training/inference systems.
• Experience in observability, performance tuning, or SRE/reliability engineering.
• Customer-facing technical experience (solutioning, support, architecture advisory).

About Nebius

Nebius AI is an AI cloud platform with one of the largest GPU capacities in Europe. Launched in November 2023, the Nebius AI platform provides high-end, training-optimized infrastructure for AI practitioners. As an NVIDIA preferred cloud service provider, Nebius AI offers a variety of NVIDIA GPUs for training and inference, as well as a set of tools for efficient multi-node training. 

Nebius AI owns a data center in Finland, built from the ground up by the company’s R&D team and showcasing our commitment to sustainability. The data center is home to ISEG, the most powerful commercially available supercomputer in Europe and the 16th most powerful globally (Top 500 list, November 2023).  

Nebius’s headquarters are in Amsterdam, Netherlands, with teams working out of R&D hubs across Europe and the Middle East. 

Nebius AI is built with the talent of more than 500 highly skilled engineers with a proven track record in developing sophisticated cloud and ML solutions and designing cutting-edge hardware. This allows all the layers of the Nebius AI cloud – from hardware to UI – to be built in-house, distictly differentiating Nebius AI from the majority of specialized clouds: Nebius customers get a true hyperscaler-cloud experience tailored for AI practitioners. We’re growing and expanding our products every day. 

The role

We’re looking for a Senior Backend Engineer to join our Storage Virtualization Team, building a distributed, fault-tolerant storage system for Nebius’ hyperscaler cloud.
You’ll work on high-performance block and filesystem storage that delivers sub-millisecond latency, millions of IOPS and terabytes per second of throughput, even in the face of hardware failures.

• Virtualization: virtio-blk and virtio-fs, QEMU and vhost-user, performance-critical I/O paths
• Networking: high-throughput VM-to-storage transport over TCP and RoCEv2 (RDMA)
• Storage systems: replication, consensus, self-healing, and data migration

• 6+ years of professional software engineering experience
• Strong knowledge of C++
• Solid understanding of algorithms and data structures
• Basic knowledge of operating system internals (I/O, memory, scheduling)
• Ability to write reliable, maintainable code and debug complex systems
• Team-oriented mindset and fluency in English

We conduct coding interviews as part of the process.

The role

We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products.

Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform.

Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense.

At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute.

What’s inside the platform

You’ll work on a system that includes (and ties together):

• Distributed Storage (Cypress): transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations.
• Compute & ETL: a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering.
• Interactive analytics (CHYT): ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place.
• Dynamic Tables: low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores.
• Orchestracto: workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native).

What you’ll do

We’re looking for engineers who combine strong systems skills with product sense: understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes — you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization.

In this role, you will:

• Design and implement new functionality in YTsaurus core (C++) with production reliability in mind.
• Build and evolve platform-level capabilities: platform architecture and operating model—multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases.
• Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation.
• Own production quality: incident response / on-call rotation, root cause analysis, and turning learnings into durable fixes.

Example projects

• Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10–100x cluster growth.
• Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection.
• Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows.
• Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability.
• Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths.

Tech stack

• Core: modern C++ (C++20, async + multithreaded primitives)
• Services & tooling: Go and Python (microservices, utilities, integration tests)

What we expect

• 5+ years of software engineering experience.
• Strong C++ skills (you’ll write core code).
• Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them).
• Experience developing and/or operating high-load, distributed services.
• Production mindset: ability to use SSH, read logs/metrics/traces, and debug distributed systems behavior.
• Solid CS fundamentals: algorithms, data structures, concurrency basics.

Nice to have

• Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems).
• Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering.
• Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs).

We conduct coding interviews as part of the process.

The role

We’re looking for a Backend Engineer to contribute to the development of our hyperscaler platform.

Your responsibilities will include:

Develop fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have: 

• 5+ years of professional software engineering experience;
• Knowledge of C++ programming language;
• Knowledge of Python, Java, and Go is a plus;
• Ability to write reliable code and dig into complex problems;
• Teamwork-oriented approach;
• Fluency in English.

Nice to have:

Experience designing high-load and scaling services.

We conduct coding interviews as part of the process.

The role 

The Data Engineering team is responsible for building and maintaining robust data infrastructure that powers analytics, and business intelligence across Nebius. We design and implement scalable data pipelines, optimize data storage and processing, and enable data-driven decision making across the organization. The team works closely with product teams and business stakeholders to ensure alignment with company goals.We are looking for a Data Engineer to design, build, and maintain our data infrastructure and pipelines. You will work on processing large-scale datasets, optimizing data workflows, and enabling analytics capabilities that support our rapidly growing cloud platform.

Your responsibilities: 

• Design, develop, and maintain scalable data pipelines.
• Build and optimize data infrastructure.
• Implement data quality monitoring and validation frameworks.
• Optimize data storage, processing, and query performance for large-scale datasets.
• Design and implement data models for analytics and reporting use cases.
• Develop tools and automation to improve data engineering workflows and productivity.
• Ensure data governance, security, and compliance standards are met.
• Participate in on-call rotation to support production data systems.

Must-haves: 

• 3+ years of experience in data engineering or related roles.
• Experience building and maintaining data pipelines using orchestration tools (e.g., Airflow, Prefect, Dagster).
• Strong proficiency in SQL and solid programming skills in Python.
• Experience with distributed data processing frameworks (e.g., Apache Spark, or similar).
• Knowledge of data modeling principles and best practices.
• Understanding of data architectures and storage systems.

Nice-to-haves: 

• Experience with real-time data streaming platforms.
• Familiarity with Infrastructure as Code tools (Terraform, etc).
• Experience with containerization (Docker) and Kubernetes.
• Knowledge of data governance and privacy frameworks (GDPR, SOC2).
• Knowledge of data quality and observability tools (Great Expectations, etc.).

We conduct coding interviews as part of the process.

The role

We are looking for a Senior Network Engineer to join our team to ensure smooth and stable operation of data center infrastructure, points of presence, and our own backbone network. The engineer will also design and develop data center networks with thousands of server ports, InfiniBand-based GPU cluster interconnect networks, and automation and management tools for such networks.

You’re welcome to work in our office in Amsterdam.

Your responsibilities will include:

• Provide technical design, operations, duties and assistance to related cross-functional teams, including the internal R&D team, HWaaS, and all-around cloud overlay & underlay network environments.
• Develop monitoring and automation tools.
• Contribute to the launch of new regions within our cloud and GPU platforms.

We expect you to have:

• Expert-level (jncie/ccie) expertise in MPLS, routing and switching Service Provider and DataCenter networks, Ethernet switching/vxlan, routing (BGP/isis), SR mpls+v6, traffic balancing/ECMP, l3 mpls VPN, and cloud overlay network technologies.
• Experience in developing and documenting a network design.
• Experience in developing plans for testing network infrastructure and vendors.
• Experience diagnosing problems with the TCP/IPv4/v6 protocol stack in a CLOS topology data center network.
• Knowledge of the design and internal architecture of modern network equipment, QoS mechanisms, and operations.
• Experience working with Juniper, Arista, Huawei, and Mellanox switches and routers.
• Working proficiency in English.

It would be an added bonus if you had:

• Working proficiency in any other European language
• Working knowledge of public clouds and GPU+infiniband networking
• Knowledge of software-defined networking overlays for the cloud environment
• Knowledge of Python, Go, or other popular programming languages in the Linux environment.
• Experience using these programming languages for task automation.

The role

Token Factory is a part of Nebius Cloud, one of the world's largest GPU clouds, running tens of thousands of GPUs. We are building a high-performance inference and fine-tuning platform designed to push foundation models to their hardware limits. Our mission is to maximize throughput, minimise latency, and optimise cost-per-token across tens of thousands of GPUs.

Some directions we are currently working on, and which you can be a part of:

• Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. Squeezing the maximum performance for a wide range of LLM architectures at scale (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-5).
• Inference engines support: Implement novel speculative decoding architectures, optimise components of various LLM designs (dense/MoE, autoregressive/parallel), and contribute to open-source inference engines.
• Low Precision Training & Inference: Design and productionise low-precision (FP8, NVFP4/MXFP4) training and inference pipelines with measurable gains in throughput and cost-efficiency.

We expect you to have:

• A profound understanding of theoretical foundations of machine learning and transformer architecture.
• Experience profiling GPU workloads using Nsight, PyTorch profiler, or similar tools
• Understanding of GPU memory hierarchy and compute/memory tradeoffs
• Familiarity with important ideas in LLM space, such as MHA, RoPE, KV-cache, Flash Attention, and quantisation
•  Understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
•  Strong software engineering skills (we mostly use Python)
• Deep experience with modern deep learning frameworks
• Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
• Strong communication and leadership abilities

Nice to have:

• Experience working with open-source inference engines (vLLM, SGLang, TensorRT-LLM), including contributions
• Experience with kernel languages or DSLs such as Triton, Cute, CUTLASS, CUDA
• A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment.
• Strong engineering skills, including experience in developing large distributed systems or high-load web services.
• Open-source projects that showcase your engineering prowess
•  Excellent command of the English language, alongside superior writing, articulation, and communication skills.

The role

We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system.

In this position, you will be responsible for:

• Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.

• Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.

• Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.

• Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.

• Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation.
  

We expect you to have:

• 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).

• 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).

• In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.

• Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python).

It would be a plus if you have:

• Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking.

• Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads).

• Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication.

• Background in Software-Defined Networking (SDN) and experience with HPC cluster networking.

• Understanding of QEMU/KVM virtualization and managing virtualized environments.

• Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems.

• Familiarity with collective communication libraries like MPI and NCCL for distributed computing. 

We conduct coding interviews as part of the process.

The role

We’re looking for a Senior Backend Software Engineer to help develop our hyperscaling platform.
We have a lot of tasks on Golang and little less on Java and Python.
You're welcome to work from our offices in Prague, Amsterdam, or Berlin— hybrid or remotely.

In this position, your responsibility will be to:
Developing fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have:

• 5+ years of professional software engineering experience
• Excellent knowledge of Golang or you are ready to quickly switch to this programming language
• Ability to write reliable code and dig into complex problems
• Teamwork-oriented approach

It would be an added bonus if you had:

• Experience designing high-load and scaling services

We conduct coding interviews as part of the process.

The role

We’re looking for a Senior Backend Software Engineer to help develop our hyperscaling platform.
We have a lot of tasks on Golang and little less on Java and Python.
You’re welcome to work from our office in Prague or in Amsterdam, hybrid or remotely. 

In this position, your responsibility will be to:
Developing fault-tolerant, reliable cloud services: cloud infrastructure, managed databases, managed Kubernetes, billing, monitoring systems, ML service and more.

We expect you to have:

• 5+ years of professional software engineering experience
• Excellent knowledge of Golang or you are ready to quickly switch to this programming language
• Ability to write reliable code and dig into complex problems
• Teamwork-oriented approach

It would be an added bonus if you had:

• Experience designing high-load and scaling services

We conduct coding interviews as part of the process.

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

One of our teams is looking for a new teammate. They are focusing on bringing AI into real products - not as a toy, but as something that actually solves problems.

You’ll be working on practical use of LLMs and AI approaches in a product environment. That means experimenting, validating ideas, and helping teams understand what works and what doesn’t. You won’t be sitting in a research silo - you’ll be working directly with teams and helping turn ideas into something usable.

If you’d like to work remotely, no problem. We’re used to hybrid collaboration based on team agreement.

WHAT WE OFFER:

• Things to be fresh. We’re building new AI products just now - and you can be part of the journey from start to finish. You’ll work across a wide range of AI disciplines, from text processing through image analysis to process automation
• No coding monkeys. We experiment, question, and figure things out.
• Work that starts with an idea and ends in a real product.
• A manager-less structure. No hierarchy, everyone has a say.
• A team that decides. Hiring, promotions, direction - all in the team.
• No bulls**t KPIs.
• Learning and knowledge sharing is part of the job, not a side activity.

WHAT WE EXPECT FROM YOU:

• Python
• Experience with at least one AI / ML-related project (school, personal, or work)
• Basic understanding of:
  • datasets
  • statistics
  • good practices in data/ML work
• Interest in AI beyond just LLMs
• Ability to explain things and share knowledge with others
• Be open-minded
• Come up with improvements and realize them
• Share your knowledge with others
• Readiness to learn new things

NICE TO HAVE:

• Experience with LLMs (RAG, agents, fine-tuning…)
• Experience with AI frameworks or tools
• Any exposure to production systems or cloud

Architect the "Source of Truth" for a Global Marketplace

At Groupon, data isn't just a byproduct—it is the product. We are looking for a Senior Data Analytics Engineer to bridge the gap between raw infrastructure and business insight. You won't just write queries; you will architect the semantic layer of our data warehouse, ensuring that every dashboard, AI model, and executive decision is built on a foundation of trust.

This is a high-impact Individual Contributor role for a builder who loves SQL, obsesses over data modeling, and wants to solve complex problems at a global scale.

The AI Advantage 🤖

We don't just analyze AI; we build with it. You will work in an AI-First environment, leveraging LLMs (ChatGPT, Claude, Copilot) daily to:

• Accelerate SQL generation and refactoring.

• Automate documentation and data lineage.

• Build specific "Feature Stores" that power our Machine Learning models.

What You’ll Build & Own

• The Gold Layer: Design and maintain clean, reusable, and documented data marts in BigQuery that serve as the single source of truth for the company.

• Pipeline Orchestration: Build robust ELT pipelines using Airflow or Keboola. If a pipeline fails at 3 AM, your code is resilient enough to handle it.

• Performance Engineering: Optimize SQL for massive scale. You understand clustering, partitioning, and execution plans to ensure we process petabytes without burning the budget.

• Data Governance: Implement automated testing (dbt-style checks) to catch data drift before it hits the dashboard.

The Tech Stack

• Core: Google Cloud Platform (GCP), BigQuery.

• Orchestration: Airflow, Cloud Composer, Keboola.

• Languages: Advanced SQL (Mandatory), Python.

• Visualization: Tableau, Looker (Knowledge of the semantic layer).

Must-Haves

• 5+ Years Experience: You have a track record in Analytics Engineering, Data Engineering, or BI Development.

• SQL Mastery: You write production-grade code. You know the difference between a query that works and a query that scales.

• Data Modeling: Deep understanding of dimensional modeling (Kimball/Star Schema) and modern data stack patterns.

• Builder Mindset: You treat data assets like software products—versioned, tested, and documented.

Ready to build the data engine that powers the future of local commerce? Apply Now.

#LI-KH1 #LI-Hybrid

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

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

Key responsibilities

System integration and support:

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

Access governance and permission reviews:

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

RBAC and ABAC modeling:

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

Required skills and experience

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

Preferred qualifications

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

Why join JetBrains?

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

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

*Some benefits may vary depending on location.
#LI-DNI 

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

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

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

As part of our team, you will:

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

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

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

Our ideal candidate would have experience with:

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

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

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

#LI-HYBRID
#LI-MR1

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

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

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

In this role, you will: 

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

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

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

It would be nice if you: 

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

#LI-KP1

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

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

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

We value engineers who: 

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

In this role, you will: 

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

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

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

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

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

How we develop JetBrains AI: 

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

#LI-KP1

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

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

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

As part of our team, you will:

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

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

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

Our ideal candidate would have experience with:

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

#LI-KP1

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

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

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

In this role, you will:

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

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

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

We’d be especially thrilled if you have: 

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

#LI-MR1

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

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

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

As part of our team, you will:

Build tools for agentic error analysis

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

Build evaluation pipelines

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

Research methods for improving agent and model behavior on Kotlin

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

Build public Kotlin benchmarks

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

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

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

Our ideal candidate would also have experience with:

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

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

Why join JetBrains? 

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

*Some benefits may vary depending on location.

#LI-DNI

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

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

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

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

What you'll do

Core responsibilities

Test automation 

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

Quality assurance 

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

Continuous improvement 

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

What we're looking for

Required skills

Technical foundation

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

Quality mindset

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

Collaboration

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

Nice to have

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

Why join JetBrains?

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

*Some benefits may vary depending on location.

#LI-DNI 

We are ShipMonk, and we provide logistics services in order fulfillment. Our main business is in the USA, but our modern platform is built by the Product Development team in Prague.

Here at ShipMonk, we process up to 100,000 orders per day in our peak season. Our book of business has more than 1,500 clients, which are small and medium e-shops, mostly based in the US. We offer the ShipMonk platform as the solution for the whole process.  It covers everything from stocking the items to shipping the ready packages to all corners of the world!

We are looking for an AI & Data Analyst in Prague to help us build our AI domain from the ground up. This is a pioneering role with full freedom to shape direction. You will drive real business value through initiatives like automated root cause analysis with AI agents. You will design the tools, processes, and projects while working closely with ShipMonk leadership. Join us in Prague and shape the future of how we use AI.

Key responsibilities

• Shape tools, processes, and bring real business value through data, AI and traditional ML.
• Take full ownership – dig in, figure things out, and get them done.
• Design and implement AI projects from prototypes to production.
• Balance technical complexity with business impact.
• Collaborate closely with business stakeholders and leadership.
• Explore and utilize our tech stack (and go beyond it when needed).

What You’ll Bring

• Experience with AI frameworks and tooling (Pydantic AI, Langfuse, or alternatives).
• Strong skills in Python and SQL, experience with analytical databases (Snowflake or similar).
• Familiarity with workflow orchestration (Airflow or similar).
• Ability to turn prototypes into production-ready solution using AI and ML.
• Pragmatic approach: balance between business value and technical complexity.
• Proactivity and autonomy – you don’t wait for perfect tasks.
• Strong communication skills for working with leadership and stakeholders.

Your team and stakeholders

For now you will be in tandem with Jana. She is an experienced go to person for our company leadership. In future you will also have other colleagues since we plan to scale this domain.

Why should you apply?

• You will attend our beautiful Karlín Offices with free snacks, grill parties and many educational events.
• This role has direct access to leadership, your work won’t get lost in layers of management.
• High autonomy from the start – no waiting for perfect tasks, you’ll own problems and solve them.
• We give you room to experiment, fail fast, and learn quickly.
• You will work in a small, tight team – your impact will be visible from the beginning.

Your key skills and capabilities: 

• Strong SQL and Python skills  

• Data modelling experience (dimensional, relational, or similar)  

• Experience building and maintaining backend systems  

• Familiarity with Microsoft Azure  

• Understanding of APIs, containers, and backend development best practices 

• Implementing cloud-native data platforms 

• Engineering scalable and reliable pipelines 

• Good knowledge of distributed computing with Spark 

• Understanding of cloud architecture principles and best practices 

• Hands-on experience in designing, deploying, and managing cloud resources 

• Agile ways of working 

• Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform 

• Monitoring and performance tuning of cloud-based applications and services  

Nice to haves:  

• Experience with Snowflake, dbt, CubeJS 

• Experience with Databricks, PySpark, ML workflows  

• Experience with containerized deployments (Docker, Kubernetes, Azure Container Apps).  

• Frontend development experience (React, Next.js, TypeScript)  

• Infrastructure-as-code (Terraform, CloudFormation) 

• Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance  

• Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining   

• ML Pipelines & CI/CD – Automate end-to-end ML workflows 

Key tasks:  

• Develop, maintain, and optimise backend services for our SaaS platform  

• Work with SQL and Python daily to build robust data pipelines and transformations  

• Model, structure, and query data to support product features and reporting  

• Integrate and maintain data ingestion flows (e.g., Fivetran, custom connectors)  

• Implement backend APIs (FastAPI) to power our web application  

• Work with our cloud environment (Azure - experience with AWS or GCP also valuable)  

• Collaborate with teammates to plan, build, and deploy features in an Agile way 

• Contribute to CI/CD workflows, monitoring, and infrastructure-as-code 

We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform.  

Your key skills and capabilities:

·      Implementing cloud-native data platforms
·      Engineering scalable and reliable pipelines
·      Good knowledge of distributed computing with Spark
·      Understanding of cloud architecture principles and best practices
·      Hands-on experience in designing, deploying, and managing cloud resources
·      Excellent python and SQL skills
·      Agile ways of working
·      Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform
·      Monitoring and performance tuning of cloud-based applications and services

Nice to haves: (MLOps):  

• Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. 
•  Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining 
• ML Pipelines & CI/CD – Automate end-to-end ML workflows 

We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform.