Top Machine Learning Jobs in Amsterdam

Own the full sales cycle for technically complex B2B deals involving APIs, on-premises deployments, and custom licensing. Manage multi-stakeholder negotiations, build strategic customer relationships, drive retention and expansion, and develop sales processes in an early-stage environment. Collaborate with engineering, research, product, solutions engineering, and legal teams while translating customer needs into product feedback.

Conduct research across the full machine learning lifecycle, including ideation, model design, implementation, evaluation, training, inference optimization, and deployment. Develop novel machine learning methods and foundation models, establish evaluation protocols, scale training with GPUs or TPUs, and improve research engineering infrastructure for rapid experimentation.

Supports Oliver Wyman’s Data and Analytics consulting team by designing analytical solutions, developing prototypes, applying machine learning and AI techniques, validating models, and assessing their effectiveness. The role involves collaborating with consultants and clients, explaining complex data science concepts clearly, and contributing to projects across financial services, sustainability, retail, transportation, and other industries. International travel and continuous technology development are expected.

Develop analytical solutions for consulting clients across financial services, sustainability, energy, retail, and transportation. Responsibilities include designing and prototyping data science solutions, applying machine learning and advanced analytics, validating models and GenAI applications, and communicating complex findings to clients and colleagues. The role involves collaboration across global teams, continuous learning, and potential international travel.

Collaborate with consultants and clients to design, prototype, validate, and implement data and analytics solutions. Projects may involve NLP, machine learning, GenAI validation, credit risk modeling, decarbonization, promotion optimization, supply chain risk, and customer churn. Explain sophisticated analytical concepts clearly, contribute to client discussions, and develop quantitative problem-solving skills in a collaborative consulting environment.

Develop analytical and machine learning solutions for global consulting clients, including prototypes, predictive models, NLP, GenAI validation, risk analytics, and optimization tools. Collaborate with clients and colleagues to explain sophisticated data science concepts, assess solution effectiveness, and deliver impactful results across industries such as financial services, energy, retail, and transportation.

Own production optimization of LLM and VLM inference systems, improving latency, throughput, memory efficiency, GPU utilization, quality, reliability, and cost. Deploy and benchmark inference engines, build compression and quantization workflows, implement acceleration techniques, diagnose serving bottlenecks, and collaborate with kernel, platform, research, product, and customer teams.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Lead end-to-end architecture, implementation, and delivery of Blue Yonder Warehouse Management and related execution solutions. Serve as the primary client contact, manage timelines, budgets, risks, and deliverables, and lead solution teams and integrations. Provide functional and technical guidance, mentor junior staff, align solutions with business objectives, and collaborate with project managers, delivery partners, and stakeholders to deliver successful client outcomes.

Lead developer relations for NVIDIA technologies across the EMEA energy and utilities ecosystem. Build strategic relationships with power, utility, grid, simulation, digital twin, and renewable energy software providers. Guide partner onboarding, integration, technical enablement, and co-innovation while identifying growth opportunities and shaping adoption strategies. Collaborate with engineering, product, marketing, and solution architecture teams; communicate technical concepts to diverse audiences; and advocate for partner feedback to influence product roadmaps.

Drive enterprise sales growth across the Benelux market by acquiring new customers, expanding existing accounts, and achieving revenue targets. Develop strategic account plans, lead complex customer engagements, present tailored AI and software solutions, and manage long-term customer relationships. Collaborate with solution consultants, customer success, professional services, marketing, partnerships, and product teams to support renewals, implementation, retention, and product feedback.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

Lead product vision and roadmap for agentic AI solutions, own the backlog, translate business needs into user stories, partner with data scientists and engineers, manage Agile delivery cycles, ensure responsible AI practices, and monitor model performance and continuous improvement.

Build end-to-end machine learning systems spanning research reproduction, model evaluation, inference infrastructure, backend services, and product interfaces. Design rigorous experiments, evaluation datasets, and verification workflows; analyze model internals; investigate provenance and evasion; and convert findings into reliable production systems with APIs, background jobs, observability, testing, documentation, and user-facing React/TypeScript experiences.

Design and lead enterprise-scale data and AI architectures for global clients. Develop prototypes and proof-of-value demonstrations, govern AI agents, integrate cloud platforms and external systems, support pre-sales, establish technical standards, and mentor teams. The role requires translating business needs into secure, scalable technical solutions while driving cloud data platform adoption, data governance, modeling, and AI-driven transformation.

Lead the strategic and technical direction of LLM and agentic AI initiatives while managing and developing a high-performing team of AI engineers and researchers. Design, develop, and deploy advanced AI solutions, mentor team members, oversee performance and capacity planning, and align AI roadmaps with business objectives. Stay current with generative AI, NLP, and autonomous systems, communicate with technical and non-technical stakeholders, and champion Agile delivery practices.

Lead the design, development, deployment, and continuous improvement of Generative AI and machine learning capabilities. Build systems involving LLMs, multimodal models, agents, retrieval, embeddings, model adaptation, and feedback-based learning. Make architectural decisions across the ML lifecycle, optimize quality, latency, cost, and reliability, and partner with research, engineering, product, and platform teams. Mentor engineers and provide hands-on technical leadership from experimentation through production.

Own the AI product vision, roadmap, prioritization, and delivery from ideation through launch. Translate business needs into technical requirements while collaborating with engineers, data scientists, marketers, and commercial teams. Drive AI adoption, monitor trends, define success KPIs, and ensure responsible, ethical, and privacy-compliant product usage.

Develop Elastic observability and security solutions for application and infrastructure teams. Build Kibana user interfaces and REST APIs, analyze IT operations data, create Elastic rules and SIEM detections, implement Elastic Security modules, and automate zero-touch deployments with Ansible. Collaborate with customers, UI teams, product management, and IT Operations while improving infrastructure automation and service quality. The role is hybrid in the Netherlands and requires Dutch nationality, a Dutch passport, and Dutch-language proficiency.

Develop Elastic-based security and observability solutions for applications and infrastructure. Build Kibana user interfaces and REST APIs, analyze IT operations data, create Elastic and SIEM detection rules, implement Elastic Security modules, and automate zero-touch deployments with Ansible. Collaborate with customers, UI teams, product management, and IT Operations to improve monitoring, security, automation, and operational efficiency.

Lead redesign of B2B underwriting models and credit frameworks, improve data analysis and processes, support multi-country product expansion, partner with Data Science on ML models, enhance reporting and KPIs, and collaborate with cross-functional teams to steer B2B risk strategy.

Lead and develop a team of Data Scientists and ML Engineers building production machine-learning systems for logistics. Drive AI adoption, roadmap prioritization, agile execution, and measurable business outcomes. Partner with Product Managers, Staff ML Engineers, and the MLOps platform team to deploy scalable solutions. The role requires deep hands-on experience with production ML, recommender systems, pricing algorithms, statistical models, and modern data and AI technologies, alongside strong people leadership and executive communication skills.

Lead Workday Compensation implementations and HCM transformations: run workshops, gather requirements, configure, test, deploy, lead workstreams, liaise with clients and teams, and apply Accenture/Workday methodologies and AI-enabled tools.

Ten-week, hands-on quantitative research internship applying mathematics, statistics and programming to market data to develop and test systematic trading strategies. Includes structured training, collaborative research projects, simulated trading, exposure to traders/researchers, and AI applications. Strong performers may receive full-time offers.

Join as a graduate quantitative researcher to design, build, test and deploy statistical and machine learning models for pricing, forecasting and signal discovery using large-scale market and unstructured data. Collaborate with researchers, traders and engineers to monitor production models, refine assumptions, and accelerate research-to-production using AI-enabled workflows.