Model Validation Senior Manager in Amsterdam

(FEQ427R544) Role Summary As a Field Engineering Manager, you will lead a high-performing team of technical pre-sales Solutions Architects (SAs) dedicated to enterprise Named Accounts across the Benelux region. You will operate at the intersection of deep technology and business strategy, driving platform adoption and enterprise AI initiatives. As a technically credible coach and AI builder , you will spend meaningful time in the field (~30-40%) partnering with customer executives and internal Sales counterparts. You will lead by example to instil an AI-Builder Mindset across your team, establish rigorous operational inspection cadences, coach SAs through complex architecture designs without taking the pen, and decisively build an elite pre-sales organisation. The Impact You Will Have Build & Scale Elite Teams: Hire, mentor, and retain exceptional Solutions Engineers/Architects in the Benelux region, establishing high standards for technical excellence, inclusive leadership, and decisive performance management. Drive AI Adoption & Capabilities: Lead by example as an AI practitioner, embedding AI tools into team workflows and driving scalable capability across the organisation. Act as a Customer Advisor: Build trusted relationships with C-level and senior technical executives across customer accounts. Translate complex platform capabilities into measurable business ROI (e.g., predictive maintenance, yield optimisation, supply chain resilience). Drive Operational Execution: Co-own regional consumption and growth targets with Sales partners. Maintain rigorous inspection cadences across pipeline health, technical validation, and account strategy. Technically Coach the Field: Serve as an architectural sounding board for your team. Diagnose platform designs, spot failure modes in distributed systems or AI infrastructure, and coach SAs to refine architectures independently. Expand Benelux Presence: Serve as a key regional leader helping build Databricks' brand and

About the Role We're looking for a Software Engineer to build the systems that treat infrastructure as software. This role owns the software state machines that provision hardware, bring it into service, and manage its full lifecycle — turning racks of GPUs into running inference clusters without a human touching a runbook. The Research and Inference team is your customer: today they file tickets and wait; the target state is that they issue a single API call to stand up, scale, or tear down a cluster, and the system takes care of the rest. The platform is manifest-driven such that teams declare the desired state of a cluster or host — shape, topology, software stack — and the system is responsible for reconciling reality to that manifest, continuously, through every stage of its lifecycle. You will design the engines that manifest the schema, the engines that execute against it, and the workflows that carry a piece of hardware or a cluster from one state to the next—taking it from bare metal to a fully functioning AI cluster for training or inference. You'll write production code which is typed, tested, versioned, and deployed through CI/CD that models infrastructure state and reconciles it, the same way a Kubernetes controller reconciles a cluster's desired state. Success looks like eliminating manual provisioning work, not documenting it better. A product mindset - you've built internal platforms or APIs consumed by other engineering teams and care about the developer experience of what you ship. You build it, you own it. You are not only responsible for delivering the software but also for operating and supporting it in production. Responsibilities Build the provisioning state machine: design and implement the software that models the full lifecycle of a physical host from discovery, inference bring-up to GPU driver/CUDA stack, health validation, and decommission/RMA — as explicit, versioned states and transitions. Build the self-service API: design declarative

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. Why you should join the AML Compliance Analytics team At Adyen, growing responsibly and protecting the financial system is core to how we scale. The AML Compliance Analytics team, a specialized unit within the Second Line AML Compliance team, provides global oversight of Adyen’s transaction monitoring framework and owns the risk behind it. You’ll work at the intersection of AML typologies, data, and analytics: independently challenging the First Line, shaping Financial Economic Crime (FEC) risk scenarios, and defending our controls to Model Validation, Internal Audit, and global regulators. In a fast-paced, high-autonomy environment, you’ll help a framework that is under continuous refinement stay ahead of emerging financial crime threats. We are looking for a driven, senior AML Compliance Analytics Expert to join our team in Amsterdam. The ideal candidate is a go-getter with a sharp analytical mind and deep FEC knowledge, someone who navigates diverse stakeholders and competing priorities with ease and delivers complex projects end-to-end. You are excited to work with a global, multicultural team, to challenge and be challenged, and to balance speed with regulatory rigor as you help set the standard for transaction monitoring at scale. Senior AML Compliance Analytics Expert Our team is encouraged to challenge each other and s

About BlockTech BlockTech is a fast-paced algorithmic trading firm trading crypto derivatives and spot across global venues, 24/7, with our own capital. Crypto is one of the few markets where a researcher can still move the edge. The data is abundant, the microstructure is novel, and the loop between an idea and live PnL is short. High-frequency options trading is where we're strongest, and we're widening our scope to include more mid-frequency work. We're looking for a senior Quantitative Researcher with a mid-frequency background to join our Amsterdam trading floor. The role You'll be in charge of developing our mid-frequency capabilities, owning the research agenda end to end, from hypothesis and dataset construction through model training and backtesting to live deployment. You'll sit with traders, researchers, and analysts, and raise the bar for research across the floor. 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 3+ years of quantitative research experience at a hedge fund, trading firm, or similar, with mid-frequency models you've taken live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, or computer science) Fluency in Python and the modern ML stack (PyTorch and/or TensorFlow, scikit-learn, NumPy, pandas) A deep grasp of overfitting, validation design, and feature engineering. You can explain why a model works, not just that it does Software engineering instincts: you write product

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

About the Role At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Hybrid at our office in Amsterdam or Remote in the UK. Responsibilites Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. Continuously improve deployment velocity, reliability, and operational efficiency through automation. Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. Strong software engineering skills in Python, Go, or Rust . Experience building platforms, automation systems, or developer infrastructure. Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. Strong systems thinkin

At Graviton, we don't believe the best trading strategies come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher, you'll work on those questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies, working alongside researchers and technologists in an environment where an idea on a whiteboard can reach live trading quickly. This isn't a role where the answers are in a textbook. The problems are open-ended, the data is enormous, and finding the answers is the job. Ideal candidates are rigorous thinkers who genuinely enjoy mathematics, programming and figuring out things that aren't obvious, based in our Singapore, London, Amsterdam or US offices. What You'll Work On You'll work across quantitative research and systematic trading, taking ideas through the full lifecycle: question, hypothesis, experiment, model, validation, strategy, production. Depending on your team and research interests, your work would include: Discovering predictive patterns and sources of alpha from billions of market events Formulating hypotheses about market behaviour and designing experiments to test them Applying probability, statistics, optimization and machine learning to build predictive models and quantitative signals for systematic trading Designing robust backtests and statistical tests to distinguish genuine signals from noise Working with large and complex datasets to uncover patterns that aren't immediately visible Investigating market microstructure and how markets behave at different timescales Evaluating strategy performance, identifying weaknesses and continuously refining models Developing research infrastructure and AI-powered tools and agents that make experimentation faster and analysis deeper Working c

(FEQ327R229) The Solutions Architect (Lakebase) team executes on Databricks’ strategic Product Operating Model that provides enhanced focus on earlier stage, highly prioritised product lines in order to establish product market fit, and set the course for rapid revenue growth. They are part of a global go-to-market team mandate, though individually will cover a specific, local region. Clients may span across one or more business units and verticals. By working in partnership with direct account teams, they will jointly engage clients, foster the necessary relationships, position in-depth the specific product line, so as to provide compelling reasons for clients to adopt and grow the usage of the given product. They understand the appropriate approach, the guardrails, and the steps needed to successfully adopt the product line, as clients deliver on their business objectives. The Solutions Architect (Lakebase) is paired with an Account Executive aligned to a given product line with specific targets accordingly. Together, they will devise and implement a strategy across their assigned set of accounts, develop presentations, demos and other assets and deliver them such that clients make an informed decision as they decide to adopt the product-line in a meaningful way. The Lakebase product-line requires the following core technical competencies: 10+ years of transactional database (OLTP) expertise across engineering, product development, administration, and pre-sales, with a proven track record of designing and delivering client-facing solutions. Credibility in influencing OLTP products with the market insight needed to shape and prioritise roadmap capabilities. Experience architecting solutions that integrate transactional data systems within broader Big Data, Lakehouse, and AI ecosystems. Infrastructure, platform and administration expertise around disaster recovery, high availability, backup and recovery, scale-out methods, identity and security ma

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.

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Role: The Client Value Partner (CVP) role is a key addition to our broader Value Engineering team and will play a crucial role in Celonis’ growth strategy. As a CVP, you will spearhead our mission of data-driven business transformation with our most strategic customers within the Digital Technology industry. You will lead extensive teams of Celonis experts to ensure the success and satisfaction of some of our top customer base on their journey to realizing value with Celonis. The CVP is the accountable lead for customer success, acting as the trusted advisor for a strategic customer. This involves engaging with C-Level Executives to collaboratively define the long-term vision for utilizing Celonis to transform their business while mobilizing the necessary Celonis resources. In collaboration with our cross-functional Celonis teams, you will drive measurable business impact across various processes and industries and accelerate the adoption of our platform. The CVP will also champion transformational initiatives across Celonis and customer accounts, fostering innovation and strategic change to maximize value and drive business transformation. We seek experienced professionals with a proven track record in managing exe

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Role: As an Applied Value Engineer, you are pushing the envelope, solving business-critical problems for our customers. Working with our most strategic global accounts, you will diagnose their strategy and key operational challenges to discover and build tailored, domain-specific use cases . You will architect and prototype state-of-the-art AI and technical solutions on the Celonis platform, demonstrate their business impact to C-suite Executives, and ensure successful implementation, adoption, and value realization. The work you’ll do: Discovery & AI Solutioning: Translate domain expertise, product knowledge, and specific customer requirements into flawless project execution. You will execute technical discovery, allowing you to prototype and build bespoke, state-of-the-art AI solutions that precisely target nuanced, industry-specific operational pain points. AI Solution Development: Drive the end-to-end execution of business-critical Proof-of-Value (PoV) projects. Deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks. Value Selling & Realization: Maintain active technical and advisory involvement with strategic accounts, e

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Value Engineering is responsible for our largest Fortune 500 customers and owns their transformation journey by working on the very frontier of what’s possible with data and AI on the Celons Platform. Partnering closely with the Sales team, Value Engineering is responsible for ensuring that the Celonis Platform is deployed to tackle the most strategic business challenges, fits into the right place in our customers’ technology stack and most importantly generates strong ROI through deep and broad deployments. The Role: As a Senior Value Engineer, you will spearhead AI and data-driven business transformation for a select number of Enterprise customers, contributing to your customer’s end-to-end value journey using the Celonis Context Model. Working alongside Lead and Principal VE's, you will combine technical execution with consulting and project management. As an AI-fluent operator, your core mandate is to orchestrate complex roadmaps and execute targeted transformation initiatives that improve how these businesses operate across their core business processes and ecosystems. The work you’ll do: Value Selling & Realization: Uncover the real issues by peeling back layers of organizational complexity. Own the Outcome from

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team Celonis Services is the delivery engine of our Celonis Customer Organization, responsible for turning the Celonis platform into measurable, business-critical outcomes for our customers. In the AI era, our role has elevated: as AI agents like our own Apollo take on more of the technical build, our people focus on the work that drives real impact—understanding our customers' business-critical problems, designing the solutions that solve them, and quantifying the value delivered. Our Deployment Engineers and Deployment Architects pair deep domain and industry expertise with serious platform mastery and AI-augmented delivery, directing agentic systems while owning the judgment, architecture, and customer relationships that AI cannot replace. We deliver faster and smarter than ever, and we own the outcome: solution go-live, solution adoption, initial value realization support and the long-term success of our customers. The Role As a Senior/ Lead AI Deployment Engineer, you are the backbone of Celonis delivery. You lead the hands-on implementation of Celonis solutions for enterprise customers, combining platform expertise with AI-augmented workflows to deliver high-quality outcomes, fast. You use Celonis’s AI deployment tools as

Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. The Team: Value Engineering is responsible for our largest Fortune 500 customers and owns their transformation journey by working on the very frontier of what’s possible with data and AI on the Celonis Platform. Partnering closely with the Sales team, Value Engineering is responsible for ensuring that the Celonis Platform is deployed to tackle the most strategic business challenges, fits into the right place in our customers’ technology stack and most importantly generates strong ROI through deep and broad deployments. The Role: As a Senior Value Engineer, you will spearhead AI and data-driven business transformation within the Public sector in the Netherlands by contributing to your customer’s end-to-end value journey using the Celonis Context Model. Working alongside Lead and Principal VEs, you will combine technical execution with consulting and project management. As an AI-fluent operator, your core mandate is to orchestrate complex roadmaps and execute targeted transformation initiatives that improve how these businesses operate across their Citizen administration and services ecosystems. The work you’ll do: Value Selling & Realization: Uncover the real issues by peeling back layers of organizational complexity. Own the Out