Top Machine Learning Jobs in the Netherlands

Leads the software engineering, applied ML, and technical product teams responsible for Protolabs’ enterprise pricing engine and supporting services. Owns the pricing capability roadmap, architecture, rules-based and model-driven decisioning systems, and production LLM capabilities. Oversees solution design, development, testing, governance, reliability, and continuous improvement while partnering with pricing analysts and service-line leaders. Hires, mentors, and develops a cross-functional technical team.

Own the strategy, roadmap, metrics, and adoption of JetBrains Context, a managed retrieval layer for AI coding agents. Partner with engineering, ML, platform, IDE, marketing, sales, and customer success teams to improve indexing, retrieval quality, integrations, reliability, cost, and latency. Define product direction, evaluate competitors, establish quality metrics, communicate with customers and developer communities, and drive enterprise adoption.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Lead a team of Data Engineers and Machine Learning specialists while setting technical direction across data platforms and production ML. Responsibilities include modernizing infrastructure, improving pipelines, deploying and monitoring models, introducing feature stores, strengthening observability, advancing marketplace models, coaching specialists, and aligning technical priorities with product and business outcomes. The role is hybrid in Amsterdam and reports to the SVP of Engineering.

Senior Solution Engineer supporting the Netherlands market by partnering with sales teams, customers, and channel partners. Responsibilities include presenting Snowflake solutions, leading demos and proofs of concept, designing architectures, developing technical champions, supporting account strategies, and communicating data and cloud technology value to technical and executive audiences.

Senior Solution Engineer supporting the Netherlands market by partnering with account sales teams, channel partners, and customers throughout the sales cycle. Responsibilities include presenting Snowflake to technical and executive audiences, delivering demonstrations and proofs of concept, designing architectures, developing technical champions, supporting account strategies, and positioning Snowflake against competing technologies. The role also involves collaborating with Product, Engineering, Marketing, and implementation partners while maintaining expertise in data, cloud, AI, and analytics technologies.

Designs enterprise SIEM and security solutions using Elastic Security and AI, delivers proof-of-value projects, supports incident response, and presents to technical and executive audiences. The role requires deep SOC workflow expertise, security architecture knowledge, forensic analysis, threat mitigation, behavioral analytics, consultative selling, and customer-facing presentations. Candidates must be fluent in Dutch and willing to travel 30–50% of the time.

Optimize large-scale ML inference systems for throughput, latency, cold-start time, and cost per token. Tune SGLang, vLLM, and TensorRT-LLM across GPUs and distributed clusters; improve batching, scheduling, KV caching, quantization, weight loading, JIT caching, and multi-node inference. Profile and instrument systems to validate performance gains, eliminate storage and networking bottlenecks, and establish technical direction through reproducible benchmarks and experiments.

Summer intern supporting computer vision and multimodal AI research for medical imaging and video. Responsibilities include interviewing clinical stakeholders, identifying business value, developing and evaluating computer vision models, extracting insights from reports, and communicating technical findings. Work covers modalities including endoscopy, ultrasound, X-rays, dermatology images, retinal OCT, and histopathology.

Deploy and operationalize machine learning models, maintain Mollie’s GCP-based ML platform, and build production-grade Python and Terraform solutions. Responsibilities include CI/CD pipelines, Kubernetes model serving, MLOps standards, observability, monitoring, automated retraining, and hosting AI and generative AI tooling. The role collaborates with machine learning scientists and engineering teams to deliver scalable, reliable ML solutions.

Drive enterprise sales growth for IQVIA’s AI-powered pharmacovigilance and drug safety technology across EMEA. Responsibilities include prospecting, developing strategic accounts, managing the full sales cycle, exceeding quotas, engaging senior safety stakeholders, and collaborating with product, consulting, hosting, and managed services teams. The role requires experience selling complex SaaS, technology, consulting, and managed services solutions to pharmaceutical, biotech, medical device, and clinical research organizations, with strong knowledge of drug safety and pharmacovigilance.

Develop and deploy spatial perception models for ADAS/AD, including BEV and occupancy-based architectures. Lead large-scale distributed training, synthetic data validation, model quantization, compression, and edge optimization for automotive SoCs. Translate research into production pipelines, benchmark accuracy and performance, conduct experiments, and build regression testing. Collaborate with research and engineering teams while mentoring junior engineers and maintaining high standards for code quality and documentation.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop and deploy domain-specific language models through pre-training, fine-tuning, and post-training. Build distributed multi-node GPU training infrastructure, prepare large-scale datasets, generate synthetic data, optimize training stability and throughput, and create evaluation frameworks. Apply reinforcement learning techniques such as RLHF, DPO, and GRPO while translating research into reliable production systems used by millions of users.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.

Develop and improve live trading systems, research infrastructure, automated strategies, alpha-generation processes, and machine-learning research and simulation platforms. The role involves writing production software primarily in C++, solving complex algorithmic and numerical problems, designing distributed systems, working within large codebases, and deploying software used to analyze petabytes of data.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Perform multilingual legal data collection, evaluation, and annotation for AI-powered contract management platforms. Analyze clauses, obligations, and terms in international business agreements; participate in onboarding, calibration, and quality reviews; and collaborate within secure client environments. Requires contract or legal expertise, strong contract interpretation skills, and fluency in English and Dutch. Prior data annotation or machine learning evaluation experience is preferred.

Owns the architecture and technical direction of algorithms for data conditioning, processing, and measurement reconstruction. Translates engineering requirements into algorithm designs, defines CPU/GPU needs, establishes performance criteria, and develops the algorithm roadmap. Provides technical leadership, mentoring, and guidance to algorithm engineers while collaborating with the Software Architect on engineering standards, reproducibility, testing, and code quality.

Leads execution research across two equity markets, setting strategy and research roadmaps for trading algorithms. Applies statistics, stochastic calculus, machine learning, and high-frequency time-series analysis to model market dynamics and optimize latency-sensitive decisions. Rapidly tests and deploys models in production while managing and mentoring researchers and collaborating with engineers and analysts. The role is based primarily in Amsterdam with relocation support.

AI/ML Engineers will build and deploy AI-native products, autonomous agents, LLM applications, RAG systems, and production ML pipelines. Responsibilities may include integrating AI into crypto infrastructure and consumer products, fine-tuning and evaluating models, optimizing inference, and developing agentic workflows and machine-to-machine payment systems. Engineers will work end-to-end with high-ownership teams in fast-moving environments.

Own enterprise customer relationships from kickoff through adoption and ongoing value realization. Lead success plans, QBRs, executive conversations, escalations, stakeholder alignment, training, and strategic recommendations. Translate technical capabilities and performance data into business outcomes such as revenue, conversion, and customer experience. Partner with Account Management to support retention and expansion while improving scalable onboarding and support processes.

Drive business development and close high-value enterprise deals with global biotech and biopharma accounts across Europe. Own strategic customer relationships, deliver recurring revenue, partner with technical and customer success teams on complex proposals, provide market insights for product direction, build industry credibility, and improve enterprise sales processes and playbooks.