Tech Lead Machine Learning Engineer

Aimlroles; Amsterdam; On-site; EUR 120,000 - 180,000; Full time

Job summary

eBay's Foundation Models team is building next‑generation Generative AI capabilities that power customer‑facing experiences at global scale. We’re seeking a Machine Learning Engineer, Generative AI - Tech Lead to own from experimentation through production, combining ML with software engineering and technical leadership.

You will work with applied researchers, engineers, product teams, and AI platform teams to shape approaches, lead execution, and deliver scalable AI capabilities that deliver

Qualifications

• Minimum 5 years of hands-on experience developing and deploying machine learning systems.
• Strong expertise in modern ML and areas such as LLMs, multimodal models, NLP, agents, retrieval.
• Experience across the ML lifecycle: training, evaluation, deployment, inference, monitoring.
• Strong software engineering in Python with ML frameworks like PyTorch.
• Demonstrated technical leadership and architectural decision-making.

Responsibilities

• Lead the technical design and delivery of Generative AI capabilities from experimentation to production.
• Build systems with LLMs, multimodal models, agents, retrieval, embeddings, and learning from feedback.
• Make architectural decisions across data, training, deployment, and monitoring.
• Collaborate with researchers and engineers to translate research into production capabilities.
• Improve model and system quality while balancing latency, cost, and reliability.
• Mentor engineers and collaborate across research, product, and platform teams.

Skills

Hands-on ML

Python programming

PyTorch

ML lifecycle

Technical leadership

Tools

PyTorch

Kubernetes

Job description

At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

At eBay, we’re more than a global ecommerce leader. We’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and reinventing the future of ecommerce for enthusiasts.

About the team and the role

The Foundation Models team builds next-generation Generative AI capabilities and products that power intelligent experiences across eBay at global scale. We work across the full AI lifecycle, from model development and experimentation to evaluation, optimization, productionization, and integration into customer-facing products and platform capabilities.

We are looking for a Machine Learning Engineer, Generative AI - Tech Lead to join the team as an individual contributor. You will take technical ownership of Generative AI capabilities from experimentation through production, combining hands-on machine learning and software engineering with technical leadership. Working closely with applied researchers, engineers, product teams, and AI platform teams, you will help shape technical approaches, lead execution, and build scalable AI capabilities that deliver measurable impact for eBay customers.

This is a hands‑on technical leadership role for someone who combines strong machine learning expertise with solid software engineering judgment and enjoys turning advances in Generative AI into reliable products and capabilities.

What you will accomplish

• Lead the technical design and delivery of Generative AI and machine learning capabilities, taking them from experimentation and prototyping through production deployment and continuous improvement.

• Build systems involving LLMs, multimodal models, agents, retrieval and context, embeddings, model adaptation, and learning from feedback, while remaining hands‑on in implementation and experimentation.

• Make technical and architectural decisions across the ML lifecycle, including data, model training and fine‑tuning, evaluation, deployment, inference, monitoring, and continuous improvement.

• Partner with applied researchers and engineers to translate promising research into scalable production capabilities, guiding technical execution and helping others solve complex implementation challenges.

• Drive improvements in model and system quality while balancing latency, cost, scalability, reliability, maintainability, and observability in production.

• Collaborate across research, engineering, product, and platform teams, mentor other engineers, and contribute to strong technical, engineering, and experimentation practices.

What you will bring

• Minimum 5 years of hands‑on experience developing and deploying machine learning systems, with a track record of owning significant ML capabilities from development through production.

• Strong expertise in modern machine learning and experience in one or more areas such as Large Language Models, multimodal models, NLP, agents, retrieval, model adaptation, or learning from feedback.

• Experience across the ML lifecycle, including model training or fine‑tuning, evaluation, deployment, inference, monitoring, and performance optimization.

• Strong software engineering skills, particularly in Python and modern ML frameworks such as PyTorch, together with experience designing scalable, reliable, and maintainable production systems.

• Demonstrated technical leadership, including making architectural decisions, driving technical execution, mentoring others, and navigating tradeoffs across model quality, latency, cost, and reliability.

• Ability to independently lead complex technical problems and collaborate effectively across research, engineering, product, and platform teams to deliver measurable customer and business impact.

Additional Details

eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status.If you have a need that requires accommodation, please contact us at [e-mail]. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities.

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