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Top Machine Learning Jobs in Amsterdam
The VP of Engineering will lead and mentor teams in machine learning and AI, oversee the ML platform, manage production systems, and drive innovation in ML practices. They will ensure alignment with the company's goals and foster a high-performance culture, focusing on efficient and robust solutions. The role also involves keeping the team updated on industry advancements and integrating leading research into initiatives.
As a GenAI Architect at ServiceNow, you will drive customer outcomes through hands-on delivery of GenAI capabilities, provide technical advisory, and ensure effective utilization of ServiceNow technologies. You will collaborate with cross-functional teams and contribute to thought leadership while staying updated with industry trends to enhance customer satisfaction and business growth.
Seeking an experienced Product Manager to lead the insights and performance management products of a Risk & Revenue optimization suite at a financial technology platform. Responsibilities include defining success metrics, building data products for merchants, and collaborating with cross-functional teams.
The Machine Learning Engineer in the MLOps team will develop, deploy, and operate MLOps tooling and services, handle model training and tracking, ensure stable model deployment, and oversee infrastructure scalability while collaborating with data science teams.
As a Machine Learning Engineer, you will develop large-scale distributed training pipelines, build low-latency inference systems, optimize libraries for performance, and collaborate on ML experiments, all to drive innovations in high-frequency trading.
The Industry Solution Director is responsible for leveraging technical and domain expertise to apply C3 AI solutions in complex predictive and prescriptive scenarios, driving projects from conception to implementation. Key responsibilities include client communication, scoping workshops, data architecture design, and collaboration with product teams to enhance application functionality.
As a Senior ML Engineer, you will lead the development of the company's computer vision capabilities, managing data labeling, building ML training pipelines, and ensuring models are deployed and maintained effectively to support key client features.
As a Chapter Lead for LLMOps, you are responsible for both managing a diverse team and contributing to the delivery of analytics projects. You will oversee team skills and allocation for product delivery, promoting career development and engagement among chapter members while being an expert in Data Science craftsmanship.
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As a Machine Learning Intern, you will work on training ML trading models, automating workflows, and improving the GPU hardware cluster. You'll receive training and mentorship while contributing to projects that advance trading strategies.
The Head of Data at Marktplaats is responsible for developing data capabilities and driving a data-driven culture. This role involves leading a team, overseeing data strategies, ensuring data privacy and governance, and implementing machine learning solutions. The position requires collaboration with various teams to align data initiatives with business goals while mentoring data professionals and managing significant data projects.
The AI/Machine Learning Software Engineer will be responsible for applying AI solutions in the learning sector, collaborating with product owners, creating data pipelines for AI/ML, documenting systems, and exploring new technologies. The role emphasizes teamwork, innovation, and the application of generative AI in various products and features.
As a Senior Software Engineer in the TractoAI team, you will improve the YTsaurus core, design new features and microservices, address performance issues and collaborate with the SRE team for system stability in a large-scale distributed environment.
As a Senior Data Science Consultant, you will lead transformation projects focused on predictive modeling, machine learning, and big data processing. Responsibilities include developing innovative data science solutions, collaborating on business development, and providing insights using econometric methods and optimization techniques.
The Research Engineer at Autodesk will lead engineering projects focused on data acquisition, processing, and experimentation to build ML-powered product features. This role involves organizing diverse datasets into unified formats suitable for machine learning while collaborating closely with researchers. Responsibilities include developing pipelines, conducting experiments, and ensuring data compliance.
The Engineering Manager will lead a cross-functional team of engineers and data scientists focused on improving translations using AI and ML. Responsibilities include managing the technical roadmap, mentoring team members, ensuring best practices in software development, and collaborating with product management to meet business goals.
As a Staff Machine Learning Engineer at Mozilla, you will lead the development of Generative AI solutions for Firefox, collaborating with various teams to design, build, and integrate machine learning models. Your responsibilities include creating infrastructures for model training and inference, implementing validation processes, and optimizing model performance in production environments.
As a Senior Product Manager, you will shape and execute Catawiki's personalization and machine learning strategy for search and ranking, ensuring a tailored user experience. You will collaborate with cross-functional teams to deliver innovative features, drive experimentation, own performance metrics, and ensure a user-centric approach in the Demand vertical.
As an Engineering Manager, you will lead a team to build scalable infrastructure for the Databricks platform, managing engineering resources and ensuring high standards of technical excellence. You will support team members in career development and coordinate projects across teams, while collaborating with product leadership to define long-term roadmaps.
As an Engineering Manager, you will lead multiple product teams focused on vegetation management and data ingestion by managing a team of engineers. You will foster a collaborative environment, provide support and coaching, make strategic technical decisions, and improve engineering practices while aligning with product managers' goals.
As an Engineering Manager, you will work as a Senior Software Engineer and manage a group of engineers, developing AI-powered architecture design products while fostering team growth. You will engage in technical work, collaborate as part of product teams, and help build a solution-focused culture within the organization.
The Senior Technical Product Manager will oversee the ML/AI product lifecycle, managing product backlogs, collaborating with cross-functional teams, and ensuring product delivery for leading AI companies. The role requires technical expertise in ML infrastructure, product innovation, and customer engagement.
As a Senior ML Platform Engineer, you'll enhance the ML platform to support research teams, managing cloud infrastructure and tooling for data collection and model training. You will ensure seamless operations for researchers by maintaining and improving the infrastructure for GPU clusters in a cloud environment.
As a Machine Learning Engineer at Autodesk, you will develop ML-powered product features, collaborate on cutting-edge research projects, construct ML pipelines, process data, and analyze errors for solutions. You will work closely with researchers and engineers to document methods and results effectively.
The Senior Machine Learning Engineer will lead the design and implementation of advanced machine learning models focusing on NLP and LLM technologies. Responsibilities include developing efficient data processing pipelines, performing large-scale data analysis, and collaborating with teams to optimize workflows in the education and research sector.
As a Presales AI/ML Engineer at Neptune, you'll be presenting the product capabilities to AI research and ML teams globally, crafting compelling narratives to accelerate their work and help them achieve AI breakthroughs.
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