Director, Machine Learning Research (Product)

Why work at Nebius
Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we work
Headquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

The role 

We are looking for a Director, Machine Learning Research (Product) — a senior, customer-facing ML research leader who will keep Nebius at the forefront of modern machine learning and translate cutting-edge advancements into product direction, platform capabilities, and measurable customer success. You will be a machine learning researcher first, with a strong ML and data foundation, operating at the intersection of Product, Engineering, and Strategic Customers.

In this role, you will continuously deep dive into the evolution of state-of-the-art ML pipelines — including training, inference, fine-tuning, evaluation, data workflows, and tooling — and convert those insights into clear product requirements and priorities, practical reference architectures for real-world workloads, and a credible, forward-looking technical point of view that strengthens Nebius both internally and within the broader ML community.

This role is US- remote.

Your responsibilities will include: 

• Drive forward-looking ML research to shape Nebius’ AI platform and PaaS roadmap, translating frontier developments into clear product direction and priorities.
• Convert state-of-the-art ML pipeline insights into actionable requirements, reference architectures, benchmarks, and gap analyses.
• Partner cross-functionally with Product, Engineering, and ML teams to align platform capabilities with emerging ML workloads and best-practice stacks.
• Build strategic collaborations with universities, research labs, and the broader ML ecosystem to accelerate innovation and credibility.
• Establish quality standards for ML-enabled services, including evaluation rigor, reproducibility, reliability, and responsible ML practices.
• Engage strategic customers to understand complex ML scenarios and translate them into clear functional and non-functional requirements.
• Provide senior technical leadership during evaluations, architecture reviews, and escalations, ensuring customer realities inform platform decisions.
• Articulate and communicate a clear vision for AI-enabled applications and the infrastructure stack required to support them, influencing both technical and executive audiences.  

We expect you to have: 

• 10+ years of experience in machine learning research and/or applied ML (industry, academia, or hybrid), with a strong track record of staying current with the research frontier.
• 5+ years operating as a senior technical leader (Staff/Principal/Director-level), shaping direction across multiple teams and stakeholders.
• Proven ability to translate research insights into tangible product or platform impact, including requirements, roadmaps, reference architectures, and evaluation standards.
• Experience engaging strategic customers or external partners in deep technical discussions, converting ambiguous goals into clear, actionable requirements.
• Demonstrated collaboration with universities or research labs through joint projects, partnerships, supervision, publications, or advisory roles.
• Strong technical communication record, including internal knowledge-sharing, external talks, writing, or publications that establish credibility. 

It will be an added bonus if you have: 

• Experience working with ML at scale, including large training runs, high-throughput inference, or performance-sensitive pipelines, even if not directly owning the infrastructure.
• Familiarity with modern ML ecosystems and tooling (e.g., PyTorch and distributed training/serving stacks) and their application in real-world production workflows.
• Experience defining, implementing, or improving evaluation practices, including benchmarking, model quality metrics, offline and online evaluation, and reproducibility standards.
• Prior experience in a field-facing technical leadership role (e.g., Field CTO, Principal Architect, Technical Advisor), partnering closely with GTM and Product teams.

What we expect you to have (skills & traits)

• ML researcher mindset: ability to evaluate new ideas critically, reproduce/validate claims, and separate signal from hype.
• Strong foundation in machine learning and data (modeling, training dynamics, evaluation, dataset considerations, experimentation practices).
• Ability to translate deep technical concepts into clear product implications and customer-ready guidance.
• Comfort operating in a highly cross-functional environment and influencing without direct ownership.
• Strong written and verbal communication: technical docs, product-facing narratives, workshops, and executive-level discussions.

Compensation

• We offer competitive salaries, ranging from $200k- $300k base equity + quarterly performance bonuses.

What we offer: 

• Competitive salary and comprehensive benefits package.
• Opportunities for professional growth within Nebius.
• Flexible working arrangements.
• A dynamic and collaborative work environment that values initiative and innovation.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

Equal Opportunity Statement:

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply, and will be required to provide proof of employment eligibility as a condition of hire.