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.

About the Product 

Token Factory is focused on building a next-generation platform that enables companies to seamlessly integrate AI into their products and workflows. Our vision is to create a powerful, open, and scalable alternative for deploying and managing AI systems—making advanced AI infrastructure more accessible to both fast-growing startups and large enterprises. 

We work with a wide range of customers, from AI-first companies to established technology organisations, helping them run AI workloads reliably at scale. Our goal is to become a leading platform for high-performance AI inference, delivering predictable latency, strong reliability, and the ability to scale to meet demanding production needs. 

Customer feedback plays a central role in how we build—our development process is highly iterative and closely aligned with real-world use cases. 

 About the Team 

We are a fast-growing, distributed team of engineers and product professionals based primarily in Europe. The team brings together strong backend, frontend, product, and business expertise, with a shared focus on building impactful, scalable systems. 

While we initially started without deep specialisation in AI/ML, the team has rapidly grown into the  space—demonstrating strong ownership, curiosity, and the ability to tackle complex technical challenges. 

Technology & Environment 

Our work is deeply integrated with a broader cloud and infrastructure ecosystem. We primarily use Go and Python to build and scale backend systems and collaborate closely with teams focused on areas such as infrastructure, observability, billing, and AI research. 

The platform continues to evolve from a lightweight integration layer into a more comprehensive system, including custom infrastructure, optimisations, and deeper control over performance and reliability. 

What We’re Working On 

• Scaling distributed systems: Expanding our platform to handle significantly increased workloads while maintaining performance and reliability  

• Improving reliability: Enhancing system stability and uptime to meet enterprise-grade expectations  

• Optimising AI performance: Continuously adapting to new models, hardware, and runtime improvements  

• Expanding platform capabilities: Building beyond inference into broader AI infrastructure, including data pipelines, customization, and advanced usage features  

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.

Why It’s Interesting 

This is an opportunity to work at the intersection of distributed systems, cloud infrastructure, and applied AI, tackling real-world scalability challenges and shaping how companies adopt AI in production environments. 

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.

THE ROLE

The FlashArray team builds the industry’s most innovative, high-performance, and highly available portfolio of products that are designed for the most demanding mission-critical applications. While we deliver a hardware storage array, over 90% of our engineering staff are software engineers. Our customers are the most important part of our business, and they love FlashArray for its simplicity of management, the constant flow of new and exciting upgrades, and the ability to live on the cutting edge of technology while never taking downtime, ever. Most recently, we extended the value of our FlashArray capabilities into the cloud with CloudSnap and Cloud Block Store for AWS. These new innovations enable our customers to leverage the agility of the public cloud for both traditional IT and cloud-native applications.

This particular role is for a security-minded software engineer. 

WHAT YOU'LL DO

• Design and implement creative new algorithms and technologies for high-performance, highly reliable systems (think six 9’s)
• Own and deliver FlashArray product security features end-to-end, from concept to shipped product
• Analyze and solve challenging problems through persistence and insight, with an eye toward making FlashArray more secure
• Work as a team with smart peers who inspire you and who are inspired by you
• Make customers really happy, because that’s why we do what we do
• Learn a ton, whether you know a lot, or nothing about system software 

WHAT YOU’LL NEED TO BRING TO THIS ROLE...

• Years of experience using a systems programming language (e.g. C++, Java or Python, etc) 
• Natural curiosity with proven design sensibility and willingness to work in a collaborative, team oriented environment
• Experience in any number of related systems software projects e.g: Distributed systems, operating systems, Linux Kernel, Database internals, Hypervisors, Containers, Compiler Optimization, etc.
• Experience with security technologies (encryption, network security, application security, etc.) is a strong plus, but a lack of relevant work experience shouldn’t deter an otherwise qualified candidate from applying 

We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Pure’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 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 now building services and agentic tools that provide AI coding agents and end users with deeper context about codebases. Our code retrieval service already delivers meaningful improvements in agent speed and task performance, and we aim to push this further – extracting richer insights than snippets alone at the scale of several hundred thousand repositories. 

We are looking for an AI Engineer who can design and implement agentic tools from scratch, bring them to the end users, and make coding with agents smarter, faster, and more reliable.

In this role, you will:

• Translate product needs into agentic tools and services and ship them to production.
• Scale prototypes to large numbers of users.
• Improve and test our semantic search service.
• Build evaluation pipelines for code retrieval and coding task performance.

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

• At least five years of hands-on NLP experience.
• Experience in information retrieval systems.
• Strong experience in LLM prompt and tool engineering, as well as with AI agents.
• Solid programming skills in Python and/or Kotlin (and the willingness to learn the language you’re unfamiliar with).
• Experience building and operating production-grade software systems.

We’d be especially thrilled if you have:

• Experience developing in Kotlin or Java.
• Previously worked with code intelligence (e.g. AST, symbol graphs).

#LI-DNI

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

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

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior ML Researcher to develop the core methods that make Spectrum possible – novel approaches to temporal ontology extraction, contradiction detection, and semantic alignment across heterogeneous software artifacts. You will help define and execute the research agenda, while also collaborating with JetBrains Research and external academic advisors.

Your responsibilities will include:

• Developing methods for LLM-based ontology construction from code, documentation, and issue trackers, including contradiction detection and reasoning over the resulting knowledge graph.
• Creating datasets, metrics, and benchmarks that drive measurable improvements across the system.
• Prototyping and validating research ideas, then collaborating with ML and software engineers to bring them to production.
• Collaborating with JetBrains Research and external academic advisors to shape our research agenda.
• Publishing research findings at top venues and representing Spectrum in the research community.

We expect you to have:

• A PhD (or equivalent research experience) in NLP, knowledge graphs, ontology learning, information extraction, or a closely related field.
• A strong publication record in at least one of the following areas: knowledge graph construction, ontology learning, information extraction, or NLP.
• Experience applying LLMs to structured knowledge extraction tasks.
• Experience designing and running rigorous experiments, including hypothesis formulation, ablation studies, and statistical evaluation.
• Strong Python and PyTorch skills, with the ability to implement research ideas from scratch.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontology engineering, semantic web technologies (OWL, RDF, SPARQL), or ontology alignment.
• A background in code analysis, developer tools, or software engineering research.
• Experience with knowledge graph embedding methods or graph neural networks.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• Actively contributed to relevant open-source projects.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• Full support for publishing ML research and attending industry conferences.
• Collaboration with JetBrains Research and external academic advisors in the knowledge graph and ontology learning community.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• A rare applied research role where your methods ship in a real product used by software teams.

Why join JetBrains? 

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

*Some benefits may vary depending on location.

#LI-DNI

Joining Collibra’s Artificial Intelligence team

We are looking for an experienced AI Engineer who will design and deliver Artificial Intelligence solutions that improve our customers' experience and enable informed, data-driven decision making. We seek someone excited about working with cutting-edge technologies to build pragmatic, performant AI solutions. You'll collaborate with a team of outstanding builders around the world, characterized by a love for innovative technology, a desire to solve problems, and a continuous pursuit of building simple, elegant products that delight customers and simplify all levels of data engagement. You will work primarily with Data Scientists, other AI Engineers, and Machine Learning Operations Engineers, as well as teams across Collibra.

This is a hybrid role based in our Prague office. Our hybrid model means you’ll work from the office at least two days each week. This setup helps us stay connected, work more closely together, and keep making progress as a team.

AI Engineers at Collibra are responsible for

• Monitoring of the larger AI/ML landscape, including emerging techniques and current state-of-the-art approaches 
• Transforming prototypes into pragmatic, production-ready solutions which solve impactful business problems
• Creating, operationalizing, and supporting AI/ML models and visualizations to power actionable value and insights
• Evaluating algorithmic results for quality, adaptability, and efficiency
• Contributing to evolving our platforms for Artificial Intelligence and Machine Learning capabilities in support of Collibra’s data products
• Collaborating with cross-functional teams and mentoring junior engineers on AI best practices

You have

• 5+ years of experience delivering production-grade AI/ML projects related to business functions, incorporating advanced techniques (e.g., LLM-based applications, RAG systems, NLP, neural networks, recommendation engines)
• Experience with SQL and relational databases, query authoring as well as working familiarity with a variety of databases (e.g., time series, graph, vector)
• Built and deployed production code in Python with associated AI modules (LangChain, LangGraph, Pandas, Numpy, Tensorflow, etc.)
• Experience with model evaluation, testing frameworks, and validation methodologies
• You must have work authorization to work in Prague, Czech Republic
• A bachelor’s degree or equivalent related working experience is required

You are

• Deeply technical, driven, and analytical about the insights data can deliver
• Able to cut through hype and noise to identify foundational problems and build maintainable, performant solution
• Passionate about the mathematical principles powering the Generative AI revolution and how to drive sustainable value from LLMs and other GenAI technologies
• Experienced supporting diverse stakeholders and working with cross-functional teams in dynamic environments
• A clear communicator who can explain complex technical concepts to both technical and non-technical audiences
• Product-minded with empathy for end users—you consider how people will actually interact with AI features, not just technical sophistication
• Eager to both learn from others and share knowledge ; AI is evolving rapidly and no one has all the answers

Reporting to Collibra’s Senior Manager of AI Engineering, measures of success are

• Within your first month, you will familiarize yourself with the existing data platform and data products by diving into the architecture, existing products, and the Collibra platform ecosystem
• Within your third month, you will start to deliver new AI/ML features into our SaaS platform
• Within your sixth month, you will operationalize AI products into production environments and contribute to our AI roadmap

About the Role:

We’re looking for a Product Manager who operates where data, strategy, and customer value meet. You’ll own and evolve our analytics domain, shaping the tools and experiences that transform raw data into clear, actionable insight. 

As the leader of the in-product Analytics team, you’ll push an already market-leading capability further by evolving dashboards from static reporting to intelligent systems powered by trend detection, predictive forecasting, anomaly identification, AI-generated insights and prescriptive recommendations that proactively guide customer decisions.

You will own one of Wrike’s most strategically important and highly adopted feature areas, used by our most active users across more than 17,000 customer accounts. This is not incremental optimization, it’s full ownership of the analytics experience end to end, from vision and data foundations to customer-facing insight delivery. You’ll set the direction, make the trade-offs, and drive execution for a capability that directly impacts enterprise decision-making, retention, and expansion.

Our Work Style:

You will have full ownership of the analytics roadmap and prioritization, with dedicated engineering and design resources aligned to this domain. This role operates with high autonomy and executive visibility, shaping not only feature delivery but the long-term direction of analytics across the Wrike platform.

Your Impact:

• Product strategy & roadmap: define and own the long-term vision and prioritization for Wrike’s in-product analytics, with a clear mandate to evolve the experience through AI-powered capabilities such as natural language querying, automated insight generation, forecasting and intelligent recommendations.

• Dashboard & visualization experience: lead the design and evolution of intuitive dashboard experiences, including customizable widgets (charts, tables, calendars), dynamic filtering/parameters, calculated fields, trend views, KPI blocks, and pivot capabilities that help customers understand and act on their data.

• Analytical infrastructure: Ensure the reliability and scalability of the data foundation powering customer-facing analytics, including well-structured data models, performant pipelines, real-time synchronization where applicable, and precise aggregation logic. Own and manage strategic partnerships with analytics technology providers such as Sisense and Snowflake to guarantee seamless integration, performance, and long-term platform evolution.

• Stakeholder engagement & adoption: Work with UX research, customer success, sales and enterprise customers to validate dashboard use cases, gather feedback on analytical needs and pain points, and drive adoption and value realization of analytics capabilities.

Your Qualifications:

• Experience: 4+ years of product management, preferably with SaaS products, with a strong track record in customer-facing analytics or reporting. 
• Customer-Centric Mindset: Strong empathy for customers and a passion for delivering exceptional user experiences.
• Product Discovery: You are experienced in conducting market research and user interviews to identify customer needs and pain points. You are also experienced in testing and validating potential solutions with real users to ensure that they effectively address the identified needs.
• Practical AI experience: Hands-on experience with leveraging AI technologies to streamline work and experience with the creation of AI-powered features.
• Collaboration Skills: Ability to work well with cross-functional teams and communicate effectively with many partners across different parts of the organization.

Why this Role is Unique:

• Intelligence transformation: lead Wrike’s evolution from reporting dashboards to proactive, AI-powered decision support.
• Strategic area ownership: Own a highly adopted, business-critical product area used across 17,000+ customer accounts.
• End-to-End scope: Shape everything from customer-facing insight experiences to underlying data models, pipelines, and strategic analytics partnerships.
• High autonomy, high visibility: Drive roadmap and long-term direction with dedicated resources and meaningful executive exposure.

Why Join Wrike?

• 5 Weeks of paid vacation
• Sick Leave Compensation 
  • 5 Paid Uncertified Sick Days
  • 2 weeks fully paid w/ medical certificate, additional 
  • 4 weeks paid at 80% salary rate
• Parental Leave (fully paid): 18 Weeks Maternity / 4 Week Paternity 
• 2 Volunteer Days
• Meal Vouchers (CZK 220 per working day)
• Annual Prague Travel Card (Lítačka)
• Hybrid Working Model
• Benefit budget with flexible options, including a MultiSport card, Canadian Medical membership, contributions to a pension savings plan and additional choices available through Benefit Plus

What’s next?

• Exploratory call with a Recruiter 
• Meeting with Product Director
• Panel Interview with our representatives of Engineering & Design
• Home Task
• Final Interview with CP
  
  

Your recruitment buddy will be Alexandra Vorobyova, Lead Recruiter.



#LI-AV1

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

Hello from Inbank! If you’ve ever bought something in three installments or financed your gadget purchase online or in a shop, there’s a good chance you’ve used something we built. 

Since you’re reading this, you’re probably looking around, or at least curious about what’s out there. We get it: choosing your next role is a big decision. Let’s get acquainted.

We’re not here to be another bank. At Inbank, we’re a modular finance platform helping businesses grow and customers pay with ease. We believe banking should feel invisible—an effortless layer that powers every great digital experience. Today, our financing rails are woven into the flow of 6,000+ leading retailers, giving around half a million customers a one-tap way to pay while turbo-charging merchants’ growth.

There are already 440+ of us across Estonia, Latvia, Lithuania, Poland, and Czechia, and we’re continuing to grow as we help thousands of retailers expand their business and reach millions of shoppers.

We’re looking for an autonomous, driven, and highly collaborative Business Implementation Manager to join our team in Prague. In this pivotal role, you’ll become a member of our Core Tribe, helping to scale Inbank’s product offering and operational excellence in the Czech market. As the bridge between local business needs in Czechia and our international Product and Technology teams, you will be crucial in turning market insights, local regulations, and new ideas into actionable, functioning product solutions. This role is about ownership and ensuring our embedded finance products deliver a real and measurable impact for our Czech customers and partners. If you thrive in a fast-paced environment and want to shape the future of embedded finance in Czechia, your next big challenge starts here.

Where does this role sit?

The Business Implementation Team within our Core Tribe acts as the crucial link between our products, technology, and local markets. We:

• Configure and tailor products across their entire lifecycle.
• Ensure that day-to-day business operations run smoothly, efficiently, and reliably.
• Connect the local business unit with our Product and Technology teams—promoting standardisation while addressing market-specific needs.

What will you do?

You’ll be the go-to expert for how our products function in the Czech market — the person who ensures everything works as intended and evolves as the market does.

• Own product configuration for Czechia across the full lifecycle — from initial launch to continuous optimisation and eventual phase-out (incl among others adjusting product setups when pricing, regulations, campaigns, or internal processes shift).
• Manage change effectively: adjust product setups when pricing, regulations, campaigns, or internal processes shift.
• Support day-to-day product and business operations for the Czech portfolio, with a strong focus on BNPL and lending products.
• Translate local needs into action: define market-specific requirements for Product and Tech teams and carry out business testing before releases.
• Close market gaps: lead or contribute to projects that align features, processes, and quality standards across countries.
• Own product-related documentation: configure and maintain customer-facing templates (contracts, pre-contractual info, notifications) in cooperation with our Legal and Product teams.
• Be a trusted partner for Sales and Customer Support: help teams use our products and platform effectively, provide guidance, and collect insights from the field.

Ideally, you would have:

• Proven experience in roles related to Product Operations, preferably in financial services or fintech would be an asset.
• A beneficial asset for this role would be a practical familiarity with Buy Now, Pay Later (BNPL) and consumer lending products, particularly their end-to-end lifecycle, spanning from origination through repayment and collections.
• Hands-on experience with projects or change delivery – coordinating multiple stakeholders, following timelines, and documenting decisions.
• Strong analytical thinking – you enjoy digging into logic, parameters, and edge cases.
• Comfortable working with data; basic SQL skills are a valuable advantage, but not a hard requirement. We are willing to teach simple queries.
• Excellent communication skills – able to explain complex things in simple language to different audiences (tech, legal, sales, partners).
• High level of ownership and reliability – you keep things moving and don’t drop the ball.
• Fluent Czech is essential for local market cooperation, and Fluent English (spoken and written) is required for daily work with our international teams.

You will do great here if you are a flexible, collaborative, and self-starting individual with a natural curiosity and a strong desire to understand the mechanics of the business. This role requires you to enjoy being close to both business and tech, translating ideas and regulations into precise configuration and processes, and thriving on structured work with real impact—where your changes are felt by thousands of customers. You must be comfortable taking full ownership, proactively identifying efficiency gaps using data and numbers, and possessing the flexible mindset needed to blend nicely into the local team while confidently asking questions and pushing for clarity.

At Inbank, we believe great work deserves great rewards:

• 5 additional vacation days per year to ensure you have plenty of time to recharge.
• 6 weeks of fully paid sabbatical after 4 years of working at Inbank.
• Hybrid working model with the flexibility to work from home.
• Modern office in the centre of Prague where we are always happy to see you.
• Small, friendly team that values open communication and a collaborative spirit.
• Pluxee Card with a flexible benefit budget tailored to your lifestyle.
• Meal compensation to support your daily lunch breaks.

Sounds like a fit? 

Apply, and our recruitment team will be in touch. If you’re unsure but curious, apply anyway – we’re happy to explore together. At Inbank, we strive to have an inclusive and diverse working environment, so we welcome you to apply even if you don’t match every single point but believe you’d do well in this role.