What are we looking for?

We are seeking a highly skilled and experienced Senior DevOps/Cloud Engineer/SRE with 7+ years of experience to become an integral part of our dynamic DevOps platform team. In this role, you will be instrumental in supporting cutting-edge AI SaaS and PaaS solutions.

Please note: This position may require participation in an on-call support rotation in the future.

Requirements

To be successful in this role, you should possess the following qualifications and skills:

Technical Skills:

• Education: A Bachelor's degree in Computer Science or a related field, or equivalent education and experience equating to the US equivalent of a bachelor’s degree.
• SDLC & CI/CD: 5+ years of experience with Software Development Lifecycle (SDLC) methodologies and CI/CD technologies, including hands-on expertise with at least two different CI/CD ecosystems. Optional: We also value experience with MLOps practices and their integration into CI/CD pipelines.
• Software Engineering: 3+ years of experience as a Software Engineer, with a preference for backend development experience. Nice to have: Experience with Temporal workflows.
• Networking & Operating Systems: Strong knowledge of networking principles and robust experience with Operating System concepts, backed by 5+ years of hands-on Linux administration.
• Cloud Platforms: 5+ years of in-depth experience with AWS (highly preferred) and/or GCP. Highly desired to have certifications in AWS or GCP.
• Infrastructure as Code (IaC): 5+ years of experience with IaC tools, primarily Terraform.
• Kubernetes: 5+ years of experience managing Kubernetes clusters, including practical experience with at least one cloud-managed service (e.g., EKS, GKE, AKS).
• Database Management: Strong experience with PostgreSQL.
• Troubleshooting: Proven ability to effectively troubleshoot issues across code, cloud infrastructure, networks, and operating systems.

Observability: 5+ years of experience working with observability tools, defining SLOs, designing alerts, dashboards and escalation chains.

• AI-Specific Technologies (Preferred): Given our focus on AI solutions, experience with MLOps, Nvidia NIM and relevant Nvidia certifications would be a significant asset.

Essential Non-Technical Skills:

• Requirements Elicitation: Ability to effectively gather and understand project requirements.
• Collaboration & Resilience: A highly collaborative team player with a resilient and proactive mindset.
• Organisational & Communication Skills: Self-organiSed with the ability to structure discussions effectively, ensuring focus and clarity.
• Documentation: Meticulous and thorough in creating clear, comprehensive documentation.
• Problem Solving: Adept at breaking down complex problems into manageable sub-tasks and defining actionable next steps.

At Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

#LI-FP1

About the Role

The ideal candidate will be naturally collaborative, articulate, extremely organized, have a solid technical understanding of Veeam products, and motivated by maximizing customer success and outcomes. Soft skills combined with technical skills are key in this role. You will partner with Customer Success Engineers (CSEs) and Account Executives (AEs) to drive customer outcomes across security-related products and use cases within the Veeam Data Platform (VDP). You’ll lead readiness checks, data modeling, and risk conversations with CISO/CIO stakeholders, while monitoring telemetry and maturity against the Veeam Data Resilience Maturity Model (DRMM) to optimize posture and identify expansion opportunities.

What You’ll Do

• Engage customers on security-related products, architectures, and risk topics across the Veeam Data Platform (VDP).  
• Run readiness checks and lead data modeling to validate solution design and accelerate decisions.  
• Monitor attack surfaces and vulnerabilities (including DRMM scoring), track telemetry or recurring inspection signals, report trends, and capture potential health checks.  
• Validate designs to de-risk adoption and accelerate time to value.  
• Identify and articulate expansion opportunities; review consumption trends and schedule checkpoint reviews (with or without AE coordination).  
• Engage CISO/CIO stakeholders for risk, status, and opportunity discussions; synthesize inputs from account health and CSE-led QBRs.  
• Support AEs on security- and AI-driven expansion motions; influence roadmap priorities with CSE counterparts.  
• Operate as a pooled resource covering Enterprise and Commercial-Named accounts (generally $100K+ ARR), typically at a 1 Security Success Engineer to 6–8 CSE coverage ratio.  
• Note: Not the primary owner for Onboarding motions nor directly responsible for Renewals

What You’ll Bring

• 5+ years of experience in engineering architecture for cybersecurity-related products (e.g., Security Engineer/Architect, Cloud Solution Architect, MLOps/ML Engineer).  
• Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field; advanced degree is a plus.  
• Relevant certifications (e.g., CompTIA Security+, CISSP, or equivalent).  
• Expertise in data security and governance, including DSPM/DLP; familiarity with AI/ML architectures.  
• Demonstrated ability to engage CISO/CIO stakeholders on risk, resilience, and modernization roadmaps.  
• Hands-on experience with solution design, POCs, telemetry monitoring, and maturity modeling (DRMM familiarity is a plus).  
• Strong communication, stakeholder management, and cross-functional collaboration skills.  
• VMCE certification (can be completed after joining)

What You’ll Get 

• 26 paid days off annually, plus 4 extra global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
• Paid parental, maternity, and paternity leave
• Fully covered family medical plan, dental, rehab, and vaccinations
• Life, critical illness, and disability insurance
• Employer pension contribution via PPK
• Monthly Edenred allowance of 450 PLN for meals
• MultiSport card fully covered by Veeam, giving access to sports facilities nationwide
• Up to 12 free therapy sessions annually, plus legal and financial advice
• Opportunities to learn and grow through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops and learning events like our annual Global Day of Learning

Please note: If the applicant is permanently located outside of Poland, Veeam reserves the right to decline the application for the position. Remote work is only possible for employees located in Poland. 

#LI-MP1

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

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

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

Your responsibilities will include:

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

We expect you to have:

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

Our ideal candidate would have:

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

What we offer

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

#LI-KP1

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

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

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

Your responsibilities will include:

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

We expect you to have:

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

Our ideal candidate would also have:

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

What we offer:

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

#LI-DNI

❗️Please note that this role is office based for Valencia, Spain (RAS Valencia - Servicios Profesionales de Recursos Humanos).

❗️If you need to be relocated, we take care of the process.

We are developing an innovative platform for intelligent gameplay analysis and complex in-game scenario automation. Our team builds internal tooling that bridges the gap between Computer Vision, text analysis, and modern LLM architectures to achieve deep, real-time understanding of game mechanics.

Key Responsibilities:

• Core Development: Designing and maintaining an in-house AI-powered service for intelligent automation.
• Computer Vision: Training and calibrating Object Detection and Classification models (CNNs, DETR) on unique proprietary datasets.
• Intelligent Analysis: Integrating OCR solutions and LLMs to interpret data and structure information from dynamic content.
• MLOps: Building pipelines for model retraining based on "low-confidence" predictions (Active Learning).
• Infrastructure: Containerizing solutions and ensuring their scalability and performance.

Our Tech Stack & Requirements:

• Experience: 4+ years in software development (Backend / Full Stack / SDET).
• AI/ML Background: Proven hands-on experience with Detection Transformers (DETR) or modern CNN architectures.
• LLM & Agents: Understanding of AI Agent principles; experience building tools and integrations with LLMs (LangChain, Indexing, Tool-use).
• Python: Strong proficiency in Python and experience in AI tool development.
• Engineering Excellence: Deep understanding of TDD, clean architecture principles, and database management (PostgreSQL/MySQL).
• Networking: Experience designing APIs (REST, GraphQL, WebSockets).
• English: Upper-Intermediate (technical documentation, professional communication).

Nice to Have:

• Experience with Kubernetes and Docker.
• Understanding of microservices architecture.
• Experience setting up CI/CD pipelines (GitLab CI, GitHub Actions).

Location: Poland

We are: 

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

Join RTB House and lead our AI Engineering Lab, a team dedicated to pioneering innovation and boosting engineering productivity by leveraging the latest advancements in Agentic AI. We are looking for a hands-on technical leader with a strong, traditional software engineering background.

In this role, you won't just be writing custom code from scratch. Our approach is highly pragmatic: we build internal tools, intelligent agents, and MCPs to supercharge our engineering workflows. A critical part of our philosophy is knowing when to leverage off-the-shelf products and existing frameworks versus when to architect and build custom solutions. We need a leader who can navigate this landscape and pick the absolute best solution for the task at hand.

You will:

• Lead & Mentor: Guide a small team of software engineers, fostering a culture of technical excellence, collaboration, and continuous improvement. Set and maintain high standards for code quality and system performance.
• Drive Pragmatic Architecture: Design and develop distributed systems, internal productivity tools, and multi-agent architectures. You will own the "build vs. buy/integrate" decisions - choosing the right mix of off-the-shelf AI products, APIs, and custom-built components.
• Innovate with Agentic AI: Spearhead the evaluation, prototyping, and integration of novel Agentic AI systems, LLMs, and Model Context Protocols (MCPs) to solve complex business and engineering problems.
• Own the Execution: Manage the full development lifecycle from concept to production deployment. Ensure that the solutions we deploy are reliable, scalable, maintainable, and deliver real value.
• Collaborate Cross-Functionally: Work closely with Product Manager, Engineering Managers, and broader engineering teams to align the Lab’s innovations with company strategy and platform requirements.

Desired experience:

• Strong Software Engineering Background: Minimum of 6 years of professional experience building, deploying, and operating complex, large-scale distributed systems (e.g., microservices, event-driven architectures).
• Technical Leadership: Demonstrated experience defining technical roadmaps, mentoring engineers, leading code reviews, and driving high-level architectural decisions.
• Programming Languages: High proficiency in Python is mandatory. Experience with at least one other language (such as Java, Go, TypeScript, or Scala) is highly preferred.
• Solution Evaluation: Strong intuition and experience in evaluating third-party tools, frameworks, and vendor solutions to solve engineering problems efficiently rather than always building from scratch.
• AI/ML Integration: Experience integrating large language models (LLMs) into production applications, alongside a basic understanding of the Machine Learning lifecycle and MLOps practices.

Nice to have:

• Direct experience building internal developer tools, custom Model Context Protocols (MCPs), or using Agentic AI frameworks (e.g., Vercel AI SDK, LangChain, AutoGen, Agent Development Kit).
• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Familiarity with the ad-tech industry and real-time bidding (RTB) systems.

We Offer:

• Projects focused on extreme performance and high code quality – clean code and solid code reviews are our standard.
• Collaboration within an interdisciplinary, self-sufficient team (including DevOps, database experts, backend developers, product designers, and QA engineers).
• Access to modern technologies and the opportunity to apply them in large-scale, high-impact projects.
• Cooperation based on B2B contract.
• You can cooperate 100 % remotely or choose one of our office spaces in Warsaw or Cracow.

Apply now!

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

About Us: 

Sauce Labs is the world’s largest full-lifecycle, test automation platform, and the company behind Selenium. Trusted by 80% of the world’s top ten largest financial institutions and over 300,000 enterprise users, Sauce Labs provides the only AI platform capable of turning business intent into autonomous testing and quality assurance. With a proprietary dataset of 8.7 billion test runs, Sauce Labs empowers the Fortune 2000 to bridge the gap between AI-driven code generation and enterprise-grade software quality. Learn more at saucelabs.com.

The Role:

We are seeking an innovative and experienced AI Architect to join our engineering leadership team. This is a strategic role that will be instrumental in designing and building the next generation of AI-powered features for our continuous testing platform. You will be responsible for architecting scalable and robust AI solutions that transform how our customers gain insights from their test data and production environments, and how they create tests.

Responsibilities:

• Define AI Architecture: Lead the design and architecture of cutting-edge AI/ML solutions for new product offerings, ensuring scalability, performance, quality and reliability within a cloud-native environment.
• AI-Powered Insights (Test & Production):  Architect AI systems to derive actionable insights from vast quantities of test run logs and analytics data. This includes identifying patterns, anomalies, and performance trends.
• Production Error Reporting Integration: Design AI solutions that integrate with our existing error reporting product to analyze production issues for mobile and web applications, providing deeper understanding and predictive capabilities.
• Unified Data Intelligence:  Develop architectures for combining insights from both test runs and production data, creating a holistic view of application quality and user experience.
• Automated Failure Analysis & Remediation:  Architect AI models and systems that can automatically identify failures in test runs, diagnose root causes, and suggest potential fixes or optimizations.
• AI-Assisted Test Case Generation:  Design AI-driven capabilities to assist in the intelligent generation of test cases, improving test coverage and efficiency.
• Leverage Cloud AI Platforms:  Work extensively with Google Cloud Platform (GCP) services, specifically focusing on leveraging and integrating with our self-hosted versions of Gemini Flash models for text generation and understanding.
• Data Strategy & Pipeline:  Collaborate with data engineering teams to define and optimize data pipelines, ensuring efficient data flow from sources (Snowflake, with an eye towards Google BigQuery) to AI models.

Enhance Delivery Process: Help identify the areas of opportunity for delivery process improvements through AI tools and validate the feasibility.

• Technical Leadership:  Provide technical leadership and mentorship to engineering teams, guiding them in the implementation and deployment of AI/ML solutions. Take part in AI governance projects.
• Research & Innovation:  Stay abreast of the latest advancements in AI/ML, evaluating new technologies and methodologies to continuously enhance our product offerings.
• Cross-Functional Collaboration:  Work closely with product management, engineering teams, and senior leadership to translate business requirements into technical AI solutions and roadmaps.

Required Skills:

Education & Experience:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 7+  years of experience in software development and architecture of production-grade systems.

• Extensive AI/ML Architecture Experience:  Proven experience in designing, building, and deploying large-scale AI/ML systems and platforms in a production environment.
• Cloud Expertise (GCP Preferred):  Deep hands-on experience with Google Cloud Platform (GCP) services relevant to AI/ML (e.g., Vertex AI, BigQuery, Cloud Storage, Dataflow).
• Generative AI Experience:  Practical experience with large language models (LLMs), particularly with models like Gemini Flash, and understanding of their deployment and fine-tuning (especially with regard to prompt engineering, agent orchestration, context windows management and output validation)
• Big Data & Analytics:  Strong background in working with large datasets, data warehousing (Snowflake, BigQuery), and analytics platforms.
• Software Engineering Foundation:  Solid understanding of software development best practices, scalable system design, and microservices architectures.
• Problem-Solving & Innovation:  Exceptional analytical skills with a track record of solving complex, ambiguous problems using AI/ML techniques.
• Leadership & Communication:  Excellent communication and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences, including senior leadership.
• Hands-on Capability:  While an architectural role, a willingness to be hands-on with prototyping, proof-of-concepts, and guiding implementation.
• Domain Knowledge (Highly Desired):  Familiarity with software testing, quality assurance, DevOps, or application performance monitoring.

Nice to Haves:

• Experience with MLOps practices and tools for managing the ML lifecycle.
• Contributions to open-source AI/ML projects or relevant publications.
• Advanced degree in Computer Science, AI, Machine Learning, or a related quantitative field.

We are a hybrid workplace that recognizes the importance of flexibility while valuing in-person collaboration and relationship building. As a result, Saucers located near an office location must be able and willing to come into the office.

Please note our privacy terms when applying for a job at Sauce Labs.

Sauce Labs is proud to be an Equal Opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender identity/expression/status, sexual orientation, age, marital status, veteran status or disability status.

Security responsibilities at Sauce

At Sauce, we will commit to supporting the health and safety of employees and properties, partnering with internal stakeholders to learn and act on ever-evolving security protocols and procedures. You’ll be expected to fully comply with all policies and procedures related to security at the department and org wide level and exercise a ‘security first’ approach to how we design, build & run our products and services.

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

About the role:

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

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

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

What you will do:

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

About you:

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

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

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 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.

JetBrains is evolving beyond standalone developer tools toward a unified, AI-native platform for software development.

AI is no longer just an assistant inside the editor – it is becoming an active participant in how software is planned, built, reviewed, and operated across teams and organizations. This shift introduces new challenges that cannot be solved at the level of individual tools alone: governance, security, cost control, observability, and coordinated work between humans and autonomous agents.

Our goal is to build a platform that enables companies to adopt AI in software development in a structured, scalable, and economically efficient manner without locking them into closed ecosystems. This platform will serve as the execution and governance layer for AI-driven development, deeply integrated with developer tools but designed to work across teams, products, and environments.

We are looking for an experienced ML leader who has created products with an ML backbone, weaving together research, technical excellence, and strong product focus.

We are seeking a professional who excels in three key areas: technology, product vision, and business operations. This role involves extensive cooperation with products across the company – both AI-native and just integrating AI.

In this role, you will: 

• Identify, prioritize, and champion high-impact AI projects that align with JetBrains' product strategy and deliver measurable business value.
• Lead a team of about 50 people across multiple AI initiatives, including hiring and developing team leads, ML engineers, and MLOps specialists.
• Set the technical direction for JetBrains’ ML roadmap,  translating cutting-edge AI advancements into practical product innovations.
• Ensure projects deliver on commitments and create measurable value.
• Set technical standards, architectural direction, and best practices for ML development.

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

• The ability to balance long-term R&D with short-term product needs.
• A track record of shipping production ML systems that users actually use.
• Experience building business cases for technical projects.
• A deep understanding of modern ML infrastructure, LLMs, and AI tooling.
• Outstanding stakeholder management skills and are comfortable working with senior leaders.
• The ability to thrive in a fast-paced environment, effectively managing multiple projects simultaneously.
• Excellent management and communication skills.
• Attention to detail in everything you do.

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

• Distributed training of multi-billion parameter models.
• CI systems, workflow automation, and experiment tracking.
• The Kotlin programming language.

#LI-KP1 #LI-HYBRID

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

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.