We are seeking a Senior Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time. This is a high-impact role working on a production system used 24x7, tackling challenges comparable to large-scale web search.

Your responsibilities:

• Design, train, and deploy ML models for retrieval, reranking, and search relevance in production
• Build and optimise embedding-based indexing and large-scale retrieval systems
• Develop models supporting crawling, data selection, and content understanding
• Define and improve quality metrics for agent-native search and build evaluation pipelines
• Work on systems operating at very large scale, including high-throughput query workloads
• Collaborate closely with engineering teams to integrate ML models into production services
• Analyse performance trade-offs across latency, quality, and cost
• Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems
• Contribute to product and architectural decisions in a fast-moving environment

Must-haves:

• 5+ years of experience in software engineering or applied machine learning
• Strong programming skills in Python, Go, or C++
• Proven experience deploying ML models in production systems
• Hands-on experience with retrieval, ranking, recommendation, or similar ML problems
• Strong understanding of machine learning and modern deep learning techniques
• Experience working with large-scale data systems and high-throughput environments
• Ability to design evaluation frameworks and define meaningful model metrics
• Product-oriented mindset with a focus on impact and iteration
• Strong problem-solving skills and ability to work in a distributed team

Nice-to-haves:

• Experience with search systems or large-scale information retrieval
• Familiarity with embeddings, transformers, and modern NLP systems
• Experience working on LLM-powered or agent-based systems
• Contributions to open-source projects, technical publications, or conference talks
• Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability

We conduct coding interviews as part of the process.

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.

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

We are opening a 3–6 month Early Career program within our AI R&D team. You will work alongside experienced researchers to solve challenges in LLMs, reinforcement learning, and agentic systems.

We are looking for Early talents to support research in:

• Reinforcement learning for agents and reasoning models
• Building reinforcement learning environments
• Efficient model distillation and evaluation

Your responsibilities will include:

• Assist in designing and running experiments to train LLMs and speculators for them
• Help analyze experimental results and document findings
• Write and maintain code for data mining, processing, and model evaluation
• Collaborate with the team to explore new methods in the selected research direction
• Participate in technical discussions and discuss future steps of research
• Advanced methods for efficient speculative decoding
• Inference optimization techniques

We expect you to have:

• Strong knowledge of computer science and machine learning fundamentals
• Experience with Python and familiarity with deep learning frameworks
• Ability to write clean, efficient code
• Strong problem-solving skills and a willingness to learn quickly
• Good communication skills in English
• Permitted to work in the job’s location

Nice to have:

• Previous experience with NLP/reinforcement learning/AI agents projects
• Familiarity with current LLM concepts
• Enrollment in or completion of a degree in Computer Science, AI, or a related field
• Contributions to open-source projects

What we offer

• Competitive salary and comprehensive benefits package
• Mentorship from experienced AI, ML, and cloud infrastructure professionals
• Hands-on experience with real customer workloads and production systems
• Remote work flexibility and a collaborative, supportive team environment
• Opportunity to be considered for a full-time role after the Early Talent Program

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

• Build prototypes and demos across the product portfolio — serverless inference, databases, MLflow, MLOps, and vertical use cases in Physical AI and HCLS — that become assets for sales, product, and engineering teams
• Support new customers hands-on through POC design, technical onboarding, and validation; act as the bridge between their ML team and the platform during the critical first months
• Go deep on emerging applied AI — new training techniques, inference optimizations, agentic architectures, new frameworks — and turn findings into working prototypes, writeups, and product recommendations
• Feed the product roadmap with specific, grounded feedback; be the voice of "here's what broke in three customer POCs last month and here's what needs to change"
• Develop reusable technical assets — notebooks, reference architectures, benchmark results — that reduce onboarding friction at scale

• You've fine-tuned large models, debugged distributed training jobs, built production RAG or agentic pipelines, and optimized inference on GPU infrastructure — not just read about it
• You're fluent in the modern ML stack: PyTorch, HuggingFace, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent, vector databases
• You've worked with enterprise ML teams — whether as a solutions engineer, customer engineer, or an ML engineer who collaborated closely with customers
• You read papers and implement them — not for credit, but because it's how you stay sharp
• You communicate with calibration: you can explain activation checkpointing tradeoffs to an ML engineer in the morning and the cost implication to a CTO in the afternoon

• Experience in any of our vertical domains: Physical AI / robotics / simulation, HCLS (drug discovery, medical imaging, clinical NLP), or enterprise AI application development
• Familiarity with MLOps at scale (Kubeflow, Metaflow, Argo, Ray)
• Prior work at a cloud provider or AI infrastructure company
• You've shared technical work publicly — notebooks, talks, blog posts that people actually use

• Competitive salary and comprehensive benefits package.
• Opportunities for professional growth within Nebius.
• Flexible working arrangements.
• A dynamic and collaborative work environment that values initiative and innovation.

About the Role and Team

As a Security Engineer, you’ll join our Security function and work closely with Platform Engineers, development teams, Legal, IT, Trust & Safety teams to ensure the protection of our platform, our users, and their data. You’ll help build and maintain a strong security foundation across our systems — including our emerging use of AI — making security a natural part of how we design, build, and operate at scale.

In this role, you’ll operate in a highly collaborative, engineering-driven environment where security is a shared responsibility. You’ll combine hands-on technical work with cross-functional partnership, enabling secure product development, guiding teams through best practices, and helping Catawiki maintain user trust while continuing to grow securely and responsibly in an AI-enhanced environment.

What You’ll Do

• Identify, assess, and remediate security vulnerabilities across applications, infrastructure, internal services, and AI/ML pipelines.
• Conduct secure code reviews, threat modeling, and security assessments for new features, architectural changes and legacy components.
• Implement and maintain secure storage mechanisms, encryption practices, secrets management, and key management solutions.
• Define, document, and enforce security policies, standards, and best practices throughout the software development lifecycle (SDLC), including AI-related data handling and model governance.
• Collaborate closely with Platform Engineers to integrate security into CI/CD pipelines, infrastructure-as-code, runtime environments.
• Work with Legal, IT, Trust & Safety teams to ensure compliance, support investigations, manage security requirements.
• Participate in incident response — investigate security events, triage issues, support remediation, and strengthen preventive controls.
• Raise security awareness across the company by providing guidance, training, and proactive support for secure development, AI safety, and system design.
• Contribute to long-term security strategy by evaluating emerging threats — including those involving AI — identifying opportunities for automation, and recommending new tools or processes.
  
  

Who You Are

• You have development experience in Ruby, Python, or a similar language, and you’re comfortable reviewing and contributing to backend codebases.
• You bring 3+ years of hands-on security engineering experience, ideally in a cloud-based or high-traffic environment.
• You understand application, infrastructure, and AI/ML security principles, and you can navigate risk within data pipelines and model-driven systems.
• You have strong knowledge of secure coding practices and common vulnerabilities (OWASP, SANS) across both traditional and AI-enabled services.
• You’re experienced with secure code reviews, threat modeling, and designing practical and scalable mitigations.
• You have a solid understanding of cryptography, encryption, key management, secrets handling, and secure data storage.
• You’re familiar with integrating security into modern SDLC practices — including pipelines, IaC, cloud-native environments, and emerging AI workflows.
• You communicate clearly and collaborate effectively with engineering and non-engineering teams..
• You’re proactive, curious, and comfortable driving initiatives that strengthen our long-term security posture.

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

So, what's the role all about?

We are seeking a Portfolio Sales Engineering Manager to lead a high-performing pre-sales organization with a strong focus on Agentic AI and AI-powered Customer Experience (CX) solutions across the NICE portfolio.  This is a leadership role responsible for shaping how autonomous agents, copilots, and AI-driven CX workflows are positioned, demonstrated, and delivered to enterprise customers across Western & Northern Europe.

You will lead and develop a team of Portfolio Sales Engineers, partner closely with Sales and Product leadership, act as a trusted advisor to customers and effectively articulate the value of NiCE solutions with both business and technical audiences.

How You Will Make an Impact

The Portfolio Sales Engineering Manager is a confident storyteller and hands-on leader with a strong background in solution selling and enterprise software. You will lead by example, eliminate sales obstacles through creative and adaptive approaches, and ensure consistent technical excellence across complex sales opportunities.

This role is ideal for someone who enjoys balancing people leadership, portfolio ownership and direct customer engagement, and who has a strong technical foundation with a customer-first mindset.

• Lead and manage with vision and hands-on expertise across Agentic Experience Autonomation, Workforce Empowerment and CX Engagement Orchestration solutions to deliver exceptional experiences for customers, partners, and prospects.
• Motivate and coach by example, actively engaging in strategic and high-value opportunities
• Lead the technical aspects of the sales process across discovery, solution design, demonstrations, and validation
• Ensure customer business challenges are clearly understood and mapped to value-driven NiCE portfolio solutions
• Own and elevate the technical sales motion for complex, enterprise AI opportunities.
• Act as an executive-level storyteller, translating customer business outcomes into compelling AI-driven solution narratives.
• Coach and mentor pre-sales teams to operate confidently at both strategic and technical depth.
• Provide timely and high-quality support for RFIs, RFPs, and customer technical inquiries
• Guide proof of concepts (POCs) including success criteria, AI evaluation metrics, and value realization.
• Build strong relationships with customers, partners, and internal stakeholders
• Provide structured feedback to Product and R&D based on customer and market insights to influence the product roadmap

Have you got what it takes?

• Proven leadership experience in pre-sales, solution consulting, or technical sales within enterprise software or SaaS.
• Strong hands-on experience with Conversational AI, Agent Assist, digital agents, or AI-driven CX platforms.
• Deep understanding of AI concepts such as intent recognition, dialog management, NLP/LLMs, automation workflows, and model performance KPIs.
• Exceptional storytelling and presentation skills with executive credibility.
• Ability to translate abstract AI capabilities into concrete, business-driven outcomes.
• Comfortable operating across C-level, technical architects, and operational leaders.
• Experience managing multiple complex opportunities concurrently.

Nice to Have

• Experience with CCaaS, contact centre platforms, or customer engagement technologies.
• Exposure to LLM-based solutions, prompt engineering, and responsible AI frameworks.
• Cloud platform experience (AWS, Azure, Google Cloud).
• Experience working with regulated industries such as Financial Services, Insurance, Telco, or Healthcare.
• Previous experience operating in a European or global pre-sales organisation.

Why NiCE?

NiCE is a global leader in AI-powered customer experience, operating thousands of AI-driven customer journeys every day at enterprise scale. This role offers a unique opportunity to influence how Agentic AI is adopted, trusted, and scaled across Europe, while building and leading one of the most advanced AI pre-sales teams in the industry.

Requisition ID: 10676
Reporting into: Director, Portfolio Presales
Role Type: Manager

#LI-Remote

The Role

The Nordics is one of the most exciting European markets for Gigs. With world-class fintech infrastructure, highly digitised economies, strong telecom ecosystems, and some of Europe’s most sophisticated B2B buyers, the region is a natural fit for what we’re building.

We’re looking for a Go to Market (GTM) Lead to own our Nordics strategy and execution end-to-end - from landing lighthouse customers and building operator partnerships to setting up and growing a high-performance regional team.

You’ll work closely with our VP of Growth and global leadership to establish Gigs’ presence across Sweden, Denmark, Norway, and Finland. This is a founding market role - a consultative, long-cycle deal-maker's job: you'll be convincing sophisticated fintechs and enterprises to embed an entirely new business line. High ownership, direct founder visibility, and a real mandate to build.

If you thrive in zero-to-one environments, have a strong network across the Nordic fintech, telecom, and technology landscape, and know how to pair sharp strategy with relentless execution - this role is for you.

What You’ll Do

• Own the Nordics market strategy: Define and execute Gigs’ go-to-market approach across Sweden, Denmark, Norway, and Finland, in close collaboration with global leadership.
• Drive commercial growth: Identify, negotiate, and close high-value partnerships with fintechs, and enterprise customers across the region.
• Build Gigs’ Nordics presence: Represent Gigs at key industry events, build your personal profile, and establish Gigs as a serious player in the Nordic ecosystem.
• Build and lead a team: Recruit and develop a lean, high-performance local team as the market scales.
• Connect the dots: Act as the bridge between Nordic market realities and Gigs’ global product, engineering, and leadership teams — channelling the right market insight to shape our roadmap.

What We Are Looking For

• Proven track record of launching or scaling a market or business line in the Nordics — ideally in fintech, payments, SaaS, telecom, or marketplace businesses.
• Strong commercial instincts: you can close deals, build partnerships, and spot high-value opportunities before they’re obvious.
• Deep network and credibility across the Nordic fintech and technology ecosystem — particularly in Sweden, Denmark, and Finland.
• Solid understanding of the Nordic regulatory landscape and business culture across the region’s four markets.
• Excellent communicator and relationship builder, internally and externally, across cultures and seniority levels.
• Self-starter: comfortable with high ownership, ambiguity, and fast-moving environments - you'll be writing the playbook, not inheriting one.
• AI-curious and practically so: you've meaningfully changed how you work using AI tools and agents, and you're energised by what that unlocks for a lean, high-output team.
• Fluency in English required; a Nordic language(s) is a strong plus.

Applications for this role will be reviewed in w/c 11th May 2026. We will be in touch with all candidates after that date.

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

Your Mission

As an IT Automation & Integration Engineer in the IT Systems & Services (ITSS) team, you will play a key role in driving scalable, secure, and intelligent automation across Catawiki’s internal systems. Your mission is to reduce manual work, enhance data and process consistency, and enable seamless cross-system experiences through well-designed, resilient integrations.
You’ll build smart, reusable automation workflows using both cloud-native infrastructure and modern Integration Platform as a Service (iPaaS) solutions, such as N8N. Working closely with stakeholders across IT, People, and Finance, you’ll translate business needs into system integrations that are efficient, secure, and built to scale.

This is a hands-on engineering role involving scripting (Python, Node.js), cloud orchestration, API integrations, Slack bot development, and the integration of AI capabilities using LLMs such as OpenAI.

What You’ll Do

• Design & Implement Automation Workflows: Develop and maintain automations across platforms like Okta, Jamf, Jira, Slack, HiBob, HubSpot, and Google Workspace using both custom code and iPaaS tools.
• Build and Manage System Integrations: Architect and deploy system integrations using REST APIs, Webhooks, and OpenAPI specifications, ensuring reliable and secure data flows across internal platforms.
• Automation Scripting (Python/Node.js) and iPaaS (N8N): Write robust automation scripts in Python and Node.js for complex logic. Use the N8N iPaaS platform to accelerate integration delivery, manage low-code/no-code connectors, and support event-driven workflows.
• Develop Slack Bots: Build scalable and secure Slack bots that connect to internal tools for automated actions, workflows, and notifications using Slack APIs.
• Use GCP for Backend Logic: Implement cloud-based automation with GCP services like Cloud Functions for processing, orchestration, and data handling.
• Infuse AI & LLM Capabilities: Incorporate AI-driven logic using OpenAI to enhance workflows, enable intelligent decision-making, and support natural language processing.
• Collaborate & Document: Translate business needs into technical requirements; maintain clear documentation of architecture, data mappings, automation workflows, and API logic.
• Monitor, Optimise & Secure: Monitor system health and workflow execution, troubleshoot integration issues, and enforce compliance with privacy and InfoSec standards.

What You’ll Bring

• Experience & Background
• 5+ years of experience in IT automation, system integration, or infrastructure engineering.
• Direct experience working with or managing iPaaS platforms such as Okta Workflow,  N8N, Workato, Tray.io, Boomi, Zapier, or MuleSoft. Preferably, direct experience producing production-grade automations in N8N.
• Technical Skills
• Proficient in Python and Node.js for automation and scripting.
• Proficient in using iPaaS, N8N, or any other iPaaS platforms for automations.
• Solid understanding of REST APIs, SOAP, Webhooks, OAuth2, JSON/XML.
• Familiarity with system integrations for tools like HiBob, Workday, Okta, Jamf, Google Workspace, Jira, and HubSpot.
• Cloud & Platform Knowledge
• Hands-on experience with Google Cloud Platform (Cloud Functions). Deep knowledge of Slack APIs and building internal bots for team workflows.
• AI Integration Awareness
• Experience or familiarity in integrating LLMs and AI services, including OpenAI, into automation pipelines.
• Operational & Interpersonal Strengths
• Strong analytical and debugging skills for complex, multi-system environments.
• Ability to design integrations with security, observability, and scalability in mind.
• Comfortable working cross-functionally with both technical and business teams.

Where You’ll Be 

This is a Hybrid role based in Lisbon, Portugal. You will work from our Lisbon Office at least 2 days per week.

In Return

You'll be part of an enthusiastic, highly motivated team of 850+ Catawikians.

• A competitive Annual Gross Base Salary depending on your level, competencies, and overall experience.
• Meal Allowance Card stipend per working day, in addition to salary.
• Health Insurance from day 1 (including dental coverage), with access to multiple hospitals and clinics and a vast wellness network.
• A Work From Home Allowance to help with your monthly household bills.
• Commuting between your home and our office is covered by Catawiki.
• Amazing Office right in the centre of Lisbon.

Your Mission

As an IT Automation & Integration Engineer in the IT Systems & Services (ITSS) team, you will play a key role in driving scalable, secure, and intelligent automation across Catawiki’s internal systems. Your mission is to reduce manual work, enhance data and process consistency, and enable seamless cross-system experiences through well-designed, resilient integrations.
You’ll build smart, reusable automation workflows using both cloud-native infrastructure and modern Integration Platform as a Service (iPaaS) solutions, such as N8N. Working closely with stakeholders across IT, People, and Finance, you’ll translate business needs into system integrations that are efficient, secure, and built to scale.

This is a hands-on engineering role involving scripting (Python, Node.js), cloud orchestration, API integrations, Slack bot development, and the integration of AI capabilities using LLMs such as OpenAI.

What You’ll Do

• Design & Implement Automation Workflows: Develop and maintain automations across platforms like Okta, Jamf, Jira, Slack, HiBob, HubSpot, and Google Workspace using both custom code and iPaaS tools.
• Build and Manage System Integrations: Architect and deploy system integrations using REST APIs, Webhooks, and OpenAPI specifications, ensuring reliable and secure data flows across internal platforms.
• Automation Scripting (Python/Node.js) and iPaaS (N8N): Write robust automation scripts in Python and Node.js for complex logic. Use the N8N iPaaS platform to accelerate integration delivery, manage low-code/no-code connectors, and support event-driven workflows.
• Develop Slack Bots: Build scalable and secure Slack bots that connect to internal tools for automated actions, workflows, and notifications using Slack APIs.
• Use GCP for Backend Logic: Implement cloud-based automation with GCP services like Cloud Functions for processing, orchestration, and data handling.
• Infuse AI & LLM Capabilities: Incorporate AI-driven logic using OpenAI to enhance workflows, enable intelligent decision-making, and support natural language processing.
• Collaborate & Document: Translate business needs into technical requirements; maintain clear documentation of architecture, data mappings, automation workflows, and API logic.
• Monitor, Optimise & Secure: Monitor system health and workflow execution, troubleshoot integration issues, and enforce compliance with privacy and InfoSec standards.

What You’ll Bring

• Experience & Background
• 5+ years of experience in IT automation, system integration, or infrastructure engineering.
• Direct experience working with or managing iPaaS platforms such as Okta Workflow,  N8N, Workato, Tray.io, Boomi, Zapier, or MuleSoft. Preferably, direct experience producing production-grade automations in N8N.
• Technical Skills
• Proficient in Python and Node.js for automation and scripting.
• Proficient in using iPaaS, N8N, or any other iPaaS platforms for automations.
• Solid understanding of REST APIs, SOAP, Webhooks, OAuth2, JSON/XML.
• Familiarity with system integrations for tools like HiBob, Workday, Okta, Jamf, Google Workspace, Jira, and HubSpot.
• Cloud & Platform Knowledge
• Hands-on experience with Google Cloud Platform (Cloud Functions). Deep knowledge of Slack APIs and building internal bots for team workflows.
• AI Integration Awareness
• Experience or familiarity in integrating LLMs and AI services, including OpenAI, into automation pipelines.
• Operational & Interpersonal Strengths
• Strong analytical and debugging skills for complex, multi-system environments.
• Ability to design integrations with security, observability, and scalability in mind.
• Comfortable working cross-functionally with both technical and business teams.

Where You’ll Be 

This is a Hybrid role based in Amsterdam, Netherlands. You will work from our Amsterdam HQ at least 2 days per week.

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

Eligible locations:

• USA
• Canada
• UK
• Portugal
• Spain
• France
• Italy
• Germany
• Netherlands
• Poland
• Czech republic
• Israel
• UAE

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

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

About the Role:

Solutions Architects on Planet’s Professional Services team are experienced technologists who work with customers to deeply understand their problems and make them successful users of Planet's product offerings. In this role, you will apply your remote sensing, geospatial, and scientific background, combined with deep knowledge of Planet’s technologies, to design and architect solutions that provide customers with the outcomes they need for long term value. Solutions Architects are good listeners and respected thought leaders that help guide large projects and teams to success outcomes and your efforts will be directly visible in customers' ability to make global change actionable.

This is a full-time, hybrid position and you will be required to work from one our Berlin or Haarlem office 3 days per week.

Impact You’ll Own:

• Architect, design, and pilot solutions, transforming customer requirements into robust solution architectures that align with your customer’s business and technology strategies.
• Deliver workshops, tailored demo-apps, and workflows, designing user experiences for solution prototyping and continuously improving the applications that customers experience.
• Support pre-sales and customer expansions on solution ideation and design by leveraging your remote sensing, geospatial, and geoinformatics knowledge, alongside technology experience in AI, machine learning, image processing, and geo-programming.
• Act as the technical lead in solution development teams within Agile environments, supported by project managers and software engineers who own the building of the solutions.
• Liaise with multiple cross-functional stakeholders, including product owners, technical project managers, and satellite and image quality engineers, for architecting the best solutions possible to Planet’s customers.
• Collaborate with sales, pre-sales, marketing, business development, legal, proposals, and other teams to support bidding and technical proposal writing for large civil government and commercial projects.
• Help own the customer success lifecycle from scoping and discovery, to project execution and delivery leading to customer satisfaction, value delivery and expansions.
• Champion Planet’s products and offerings in-person and via online assistance by providing training, presenting at conferences, writing technical tutorials, and publishing articles and videos.
• Interact and engage with users in Planet’s Education and Research program to source novel customer applications and unique insights.

What You Bring:

• A background in remote sensing, geoscience, or geoinformatics
• 4+ years of relevant work experience in a technical geospatial or remote sensing role.
• Bachelor’s degree in GIS, Computer Science, Remote Sensing, Geography, or a related field.
• Extensive programming ability with Python for geospatial applications, applying code best practices to process imagery, manipulate vector data, and build data pipelines.
• Experience with solution design, requirement gathering, product user story ideation, solutions design documentation, architecting and prototyping.
• Proficiency with QGIS, ArcGIS, GDAL, ENVI or other common geospatial software.
• Industry-specific knowledge and experience in domains such as forestry, natural disasters, sustainability, and agriculture.
• Familiarity with cloud-computing environments such as GCP, AWS, and Azure.
• Experience working in Agile, cross-functional teams, with knowledge and familiarity of efficient, metrics-based planning and delivery.
• Experience using AI for productivity, coding, and demo app creation (e.g., using Streamlit).
• Ability to run workshops or training sessions with users, including working directly with end-user troubleshooting.

What Makes You Stand Out:

• Advanced experience with machine learning algorithms applied to geospatial data, and the use of Claude and AI for geospatial application.
• Working knowledge of modern cloud tools and pipelines, including Google Functions, CI/CD integrations, Vertex AI and Amazon Bedrock.
• Knowledge of the Challenger methodology for liaising with clients - supporting them and helping them see what they are not seeing, especially as you guide them on the solutions journey.
• Working knowledge of JavaScript and its mapping libraries (OpenLayers, Leaflet, ArcGIS API for JavaScript) as well as web development frameworks like React.

Application Deadline:

June 29, 2026 by 11:59p / 23:59 CET (Central European Time)

Benefits While Working at Planet:

These offerings are dependent on employment type and geographical location, based upon applicable law or company policy.

• Paid time off including vacation, holidays and company-wide days off 
• Employee Wellness Program 
• Home Office Reimbursement
• Monthly Phone and Internet Reimbursement
• Tuition Reimbursement and access to LinkedIn Learning
• Equity 
• Volunteering Paid Time Off

At WPP Media, we are the global media collective of WPP, fully built for the AI era. We unite the best platform, the most talented people, and the strongest partners to create innovative solutions. Our goal? To offer brands unparalleled growth every day. This foundation is rooted in our shared core values:

We’re Extraordinary: We push boundaries, challenge conventional thinking, and break the status quo in our pursuit of innovation and growth.

We’re Open: We build trust and understanding by collaborating seamlessly—with our teams, clients, and partners.

We’re Optimistic: A 'growth mindset' is in our DNA. We embrace change as the ultimate way to bring out the best in ourselves.

Ready to lead the next wave of advertising innovation? We're looking for a: Solutions Lead | Advanced DOOH & Emerging Tech

Are you a strategic innovator ready to drive the future of advertising? Do you want to lead the charge for global brands and shape how they connect with audiences through cutting-edge technology? As our new Solutions Lead in Amsterdam, you will be the visionary behind our Advanced Digital Out of Home (DOOH) and emerging media solutions, making a tangible impact on clients like Unilever, G-star, and Netflix.

Your Mission

As a Solutions Lead, you are the architect of our future-forward media products. You won't just manage projects; you'll own the innovation pipeline, from initial concept to market-leading solution. Your time will be focused on pioneering Advanced DOOH (60%) and exploring new frontiers in commerce, gaming, and Connected TV.

• Spearhead Innovation: You will lead the design, development, and scaling of our emerging media solutions, with a heavy focus on programmatic DOOH strategies.
• Drive Strategy with Data: Through test-and-learn strategies and deep market analysis, you'll validate our value propositions and identify the trends and technologies that will define tomorrow's advertising landscape.
• Act as a Strategic Partner: You'll be the crucial link between our agencies and internal teams, building strong relationships to uncover client needs and ensure our solutions are not only brilliant but also profitable and operationally excellent.
• Own the Lifecycle: You will lead the end-to-end delivery of market-ready solutions—from Proof of Concept and validation to Go-To-Market deployment and defining the KPIs that prove our success.
• Champion Our Vision: As a WPP Media Solutions Ambassador, you'll share your expertise and best practices, elevating the knowledge of the entire organization and acting as a thought leader in your field.

Your Profile

You're not just a digital marketer; you're a strategic builder with a passion for technology and a proven track record of turning ideas into reality.

• You have a Bachelor's or Master's degree and 4-6 years of experience in the digital advertising or ad-tech space.
• You possess a deep, strategic understanding of the digital marketing ecosystem. Experience in (programmatic) Out of Home is a significant advantage.
• You're fluent with the tools of the trade; familiarity with DSPs (like Google Ads, DV360, Xandr, Amazon Ads) is a plus.
• You are a natural leader: analytically sharp, results-driven, proactive, and an excellent communicator (our working language is English).
• You thrive in a team environment but have the confidence and skill to lead initiatives independently.

What we offer

• Flexibility: The option to work from home, flexible working hours, and even work from abroad (EU).
• Growth Opportunities: Plenty of room for development in an innovative and dynamic team, with a focus on AI transformation.
• Access to M Academy: For extensive training and workshops in both hard and soft skills, including specific AI training.
• Mental Wellbeing: Access to the Headspace app.
• Salery: Range between €4000 - €5000
• Travel Allowance: Your travel expenses are fully reimbursed.
• Holiday Pay: 8% holiday pay and 26 vacation days per year (plus the option to buy 9 extra!).
• Hybrid Working Allowance: €30 net per month for full-time employment.
• Bring Your Own Device (BYOD): You'll receive a monthly phone allowance of €57.50 net.
• Lunch Facilities: Affordable lunch in our canteen and a barista for fresh coffee in our state-of-the-art 'Amsteldok' office with a stunning view over Amsterdam.
• Health Insurance: Benefit from our collective health insurance plan.

Ready to Lead the Charge?

If you're the strategic innovator we're looking for and you're ready to make your mark on the global stage, we want to hear from you. Don't hesitate! Click the 'Apply' button and send us your resume and motivation. Let's build the future of media together.

Position Overview:

As an Account Director with Diligent, you'll be at the forefront of driving revenue growth, deepening customer engagement, and shaping the future of how businesses utilise our cutting-edge solutions. Success in this role means expanding product adoption among current customers and introducing new clients to our platform. This is a high-impact, individual contributor role that demands strategic vision, proactive relationship-building, and relentless pursuit of excellence. You’ll be responsible for everything from engaging prospects and managing a robust pipeline to delivering accurate forecasts and closing deals. Acting as a trusted advisor and strategist, you’ll lead account planning, orchestrate internal collaboration, and leverage expertise to elevate customer success and revenue growth.

We’re looking for a commercially sound sales professional with a track record of exceeding targets, a natural collaborator, and someone who thrives in fast-paced, high-growth environments. If you’re driven to create value, embody a customer-first ethos, and deliver innovative solutions, this is the role for you.

Key Responsibilities:

• Proactively build a deep knowledge of and expertise in Diligent’s products, solutions, strategy and business priorities.
• Responsible for prospecting new and existing business within the designated vertical / territory for complex accounts with longer sales cycles.
• Adopts a ‘solutions’ selling approach, understanding customer needs and developing solutions through the lens of the Diligent One Platform.
• Build deep relationships with prospects and customers during interactions by being customer-focused and consistently honouring commitments and connecting the customer to internal commercial stakeholders to foster product growth.
• Develop and execute on account plans to ensure revenue targets, quota and customer business needs are met and collaborates with key stakeholders to drive integrated joint account wins for mutual business growth.
• Leads the coordination of Sales stakeholders to prioritise actions for multiple assigned accounts based on customer needs, sales generating importance, and account risks.
• Develops specialised business plans for customers that drive business outcomes to generate new business and upsells. Presents business plans to customers to generate new non-qualified opportunities.
• Create and lead feedback loop processes with product management and product marketing to communicate and relay customer pain points and feedback.
• Demonstrate Sales excellence by managing the end-to-end sales cycle from opportunity to deal close using the Diligent approved sales methodology.
• Effectively utilise sales tools to prospect new leads, schedule initial meetings, increase win rates and generate bookings.
• Accurately maintain SFDC records, forecast and report out on projected bookings, deals closed etc. on a regular basis.
• Demonstrates a deep understanding of the competitor landscape externally, including customers’ business strategy and the direction of the industry.

Required Experience/Skills:

• 7+ years of success in account management, new business acquisition, and exceeding revenue targets, ideally within highly regulated industries, SaaS or GRC space.
• The ability to build trust and influence senior leaders and stakeholders at all organisational levels.
• A passion for continuous learning and a sharp understanding of both internal products and external industry trends.
• Exceptional presentation, negotiation, and interpersonal skills that inspire confidence and drive outcomes.
• A knack for aligning technology solutions with business objectives to deliver measurable value.
• Self-motivation, resilience, and a results-driven approach to thrive in a dynamic, fast-paced environment.

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