Ml Applied Research Manager in Amsterdam

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern ML stack (PyTorch and/or

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Staff Software Engineer focusing on AI Compute in the Together Cloud org, you will set technical direction for and build major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. This is an architect-and-build role. Fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes — you'll set the architecture for these across our global and in-DC services, and be a key owner of the hardest parts, in the code as well as the design. Your designs will span the IaaS layer of a greenfield Vera Rubin data center up to the global management plane that schedules capacity across all of them. At this level the job is as much leverage as code: the standards you set and the engineers you grow decide how fast the rest of Together Cloud ships. Responsibilities Own the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that keeps

AI Engineer - FDE (AI Forward Deployed Engineer) Req ID: CSQ427R333 Location: Location: Amsterdam, Netherlands - Candidates to be based in the Netherlands region only (no remote working available from any other country) Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Reporting to: Senior Manager - AI FDE, EMEA The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTo

Req ID: FEQ327R410 The Role As a Solutions Architect in the Benelux Strategic Accounts team, you will play a lead role in driving the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialisation (archetype) and are recognised within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy with customer accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialisation (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (Delivery, Specialist & Partner Solution Architects) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales and/or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapi

REQ ID: CSQ427R198 Location: Amsterdam, Netherlands Mission The Forward Deployed AI Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services (PS) engagements to help our customers build and productionize first-of-its-kind AI applications with a focus on GenAI. We work cross-functionally with AI/ML Product, Research, and Engineering to shape long-term strategic priorities and initiatives. We are looking for a world-class leader to lead and grow our EMEA AI FDE team. In this role, you will lead customers on their AI/ML transformation with Databricks, push the boundaries of our product, recruit and develop top data scientists/machine learning engineers, and manage a portfolio of key EMEA accounts. You will report directly to the Head of EMEA AI FDE. The impact you will have: Lead and scale a world-class AI/ML professional services team, including hiring, mentoring, and building a team structure to support long-term growth and execution at scale Develop and expand executive relationships with EMEA customers and partners (including VP+, CIO/CDO-level stakeholders), acting as a trusted advisor during complex technical engagements and AI transformations Align with Field Engineering and Sales Leaders to define joint strategies for strategic accounts and ensure strong delivery coordination across functions Lead strategic AI PS initiatives, practice development, and standardised delivery processes; design scalable engagement models and reusable solutions for repeatability across the global team Shape cross-functional collaboration by influencing Product, R&D, and GTM—ensuring voice-of-customer insights and delivery learnings help inform the product roadmap and GTM strategy Own OKRs for AI-services led accounts, revenue, utilisation, and public references Represent Databricks as a thought leader in AI/ML What we look for: Extensive experience managing, hiring, and building a team of high-performing data

About the Role Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure. As a Lead/Manager, you will play a key role in building the Together cloud platform engineering team in the Netherlands. We are a highly available, global, blazing-fast cloud infrastructure that virtualizes cutting-edge ML hardware (GB200s/GB300s, BlueField DPUs) and enables state-of-the-art ML practitioners with self-serve AI cloud services, such as on-demand + managed Kubernetes and Slurm clusters. This platform serves both our internal SaaS products (inference, fine-tuning) and our external cloud customers, spanning dozens of data centers across the world. Some of what you’ll work on: Work on a distributed GPU scheduling system for the on-demand clusters product, Instant Clusters. Build out a global management plane for managing our data center compute, networking, and storage. Design and build new customer-facing cloud platform services, delivering killer enterprise AI cloud features. Hybrid working 2 days a week at our offices in Amsterdam Responsibilities Lead/Manage a team of 8 together cloud Infrastructure Engineer in Amsterdam, Identify, design, and develop foundational backend services that power Together’s commerce platform Analyze and improve the robustness and scalability of existing distributed systems, APIs, databases, and infrastructure Partner with product teams to understand functional requirements and deliver solutions that meet business needs Write clear, well-tested, and maintainable software and IaC for both new and existing systems Conduct design and code reviews, create developer documentation, and develop testing strategies for robustness and fault tolerance Participate in an on-call rotation to address critical incidents when necessary Requirements Ideally 1-2 years of leading the Infrastructure team. Demonstrable backgro

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Head of Engineering, Adyen Protect We are seeking a visionary and highly technical Head of Engineering to lead the development and scaling of Adyen Protect . Adyen Protect is our ML-first product suite designed to detect and mitigate payment fraud in real-time across billions of transactions. In this role, you will lead a specialized domain of four high-impact engineering teams dedicated to staying ahead of increasingly sophisticated global fraud networks. You will be the strategic driver behind our risk engine, ensuring that our ML models are not only accurate and performant but also transparent and actionable for the world's largest merchants. This is a role for a leader who thrives at the intersection of big data, predictive modeling, and high-availability systems. You will be responsible for ensuring that as Adyen grows, our ability to protect our merchants and their consumers remains world-class. What you’ll do: Vision & Strategy: Define and execute the technical roadmap for Adyen Protect, aligning Machine Learning capabilities with the evolving needs of global e-commerce and regulatory landscapes. Scale ML Operations: Lead four multidisciplinary teams in building and maintaining scalable infrastructure for model training, real-time scoring, and automated experimentation (A/B testing) at the millisecond level. Engineering E

About the Role Together AI is building the AI Native Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art GPU cloud infrastructure. The Together Cloud team builds the [Together GPU Clusters](https://www.together.ai/gpu-clusters) flagship IaaS product that provides high-performance, AI-ready GPU clusters through a self-serve cloud console, along with the virtualized infrastructure layer powering Together's inference, RL, and fine-tuning products. As a Senior Software Engineer focusing on AI Compute in the Together Cloud org, you will build and own major components of the next generation AI cloud platform – a highly available, global cloud infrastructure with cutting-edge virtualization of the latest ML hardware: GB300s/VRs, BlueField DPUs, InfiniBand and dual/quad-plane RoCEv2 fabrics. That virtualized computing platform powers our own SaaS products – inference, RL, and fine-tuning – and serves external cloud customers through self-serve offerings such as on-demand/reserved Kubernetes/Slurm clusters, across dozens of data centers and hundreds of thousands of GPUs. The hard problems in rapidly scaling heterogeneous GPU fleets are software problems: fully automated bootstrapping of GPU data centers, high-performance virtualization of GPU compute and DC networking without compromising isolation or portability, and fault-tolerant decentralized control planes. We solve them by building global and in-DC services, Kubernetes operators, and high-performance SDN libraries, forking hypervisors and Linux kernels, and building infra tailored to inference and fine-tuning. You'll own massive greenfield projects across their full lifecycle – scoping the problem and writing PRDs with our PMs, designing the system, and building it through to GA launch. Responsibilities Build the GPU and network virtualization stack: the hypervisor, kernel, and SDN work that makes GPU compute and DC networking high-perform

RDQ426R402 At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. As a Product Manager on the Lakeflow Jobs team , you will shape the future of data-aware orchestration on the Databricks Data Intelligence Platform. Jobs is Databricks’ built-in orchestrator, managing hundreds of millions of workloads every week with 99.95% reliability. It powers ETL, AI/ML, BI, and streaming workloads for thousands of customers. Your focus will be on evolving control-flow capabilities, authoring experiences, and observability features that allow customers to productionize workflows with best practices like source control, code promotion, and system observability. This role requires a deep understanding of orchestration workflows , data pipelines , and service reliability. You will work closely with engineers, designers, field teams, and customers to define the roadmap, drive adoption, and ensure Jobs is the best-in-class orchestration platform for modern data and AI teams. The impact you’ll have: Define strategy & roadmap: Set vision and priorities across orchestration, triggers, authoring, and observability. Translate customer needs into features and integrations that accelerate Lakeflow Jobs adoption. Drive metrics & observability: Define success metrics for adoption, engagement, and developer efficiency. Use data to guide roadmap decisions and refine the product experience. Collaborate cross-

P-1125 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 9+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 15+ years of experience building large scale distributed systems with high availability Le

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a Quantitative Research Intern, you'll spend 10-12 weeks working on research that directly shapes how we understand markets and build trading strategies. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are quantitatively sharp, practically minded problem solvers, programmers, mathematicians and scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises, discovering predictive patterns from billions of market events, designing statistical models, and applying machine learning to open research problems. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Designing experiments and backtests to evaluate hypotheses Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn how experienced researchers approach hard problems: breaking them down, questioning assumptions, and deciding based on evidence rather than intuition. You'll be paired with a mentor, reporting manager and buddy, with regular code reviews and feedback through

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Running large-scale simulations and experiments on high-performance research infrastructure Designing experiments and backtests to evaluate hypotheses Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn what changes when research meets live markets: why a result that would survive peer review can still fail as a trading signal, how costs and capacity constrain an idea that looks clean on paper, and how to tell a model that is right from one that is right for the wrong reason.

This is Adyen Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. The opportunity: We are seeking a Senior Product Manager to lead our Anti-Money Laundering (AML) detection product within Identity & Risk Intelligence. Financial crime keeps getting more complex, and as Adyen expands into new products and markets, our detection needs to scale with it - without becoming a bottleneck for growth. This role needs a Product Manager who can take a clear strategy and drive it to execution, make strong trade-offs, and build trust with Compliance and other senior stakeholders. You need a track record of building ML-driven products in a regulated environment. You'll lead a team of Data Scientists, Data Analysts and Backend Engineers, and work closely with Compliance, Operations and other product teams. What you'll do: Risk Detection & ML Modeling: Lead the build and scaling of Machine Learning models, rules and risk signals that detect financial crimes across Adyen's products, markets and customer base. Scalable, Self-Service Detection: Move financial crime detection toward a self-service framework that picks up new typologies quickly, using ML, GenAI and agentic approaches to reduce manual effort and keep pace with Adyen's growth without adding headcount. Strategy Execution & Prioritization: Own the execution of the financial crime detection strategy. Prioritize ruthlessly, make data-driven

This is Adyen At Adyen, we’re engineered for ambition. We empower our teams with the culture and support they need to own their careers. The people of Adyen are motivated problem-solvers who tackle unique technical challenges at scale, delivering innovative and ethical solutions to help businesses achieve their ambitions faster. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Senior Machine Learning Engineer Adyen is looking for a Senior Machine Learning Engineer to join our Anti-Money Laundering team in Amsterdam, someone with experience of building and operating robust machine learning systems at scale in production environments. The Anti-Money Laundering team processes a massive transaction volume (over 800B euro in H1 2026) to detect complex financial crime and cover a wide range of customer risks. We currently run a hybrid stack of business rules and machine learning models, with a clear mission to systematically reduce our dependence on static rules and transition to a modern, model-first detection engine. In this role, you will: Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment Help us upgrade an existing rules-heavy system to a modern automated AI/ML engine Collaborate with data engineers and data analysts to develop best in class Fintech models Collaborate with operations and compliance teams to ensure Adyen’s models operate worldwide without a hitch Tackle difficult technical challenges like extreme class imbalance and incomplete ground truth Support and encourage good engineering practices Who You Are: You have 7+ years of experience as an engineer working in th