Machine Learning Engineer, Next-Generation Recommendation Systems

Unity Technologies; Washington; On-site; USD 127,000 - 191,000; Full time

Benefits offered by this job

Comprehensive health insurance

Employee stock ownership

Generous vacation days

Commute subsidy

Job summary

Unity Technologies is seeking PhD graduates to push the frontier of ranking and recommendation with LLMs and RLHF on a production-scale ad platform. You will design models, build user understanding systems, and optimize bidding dynamics, collaborating across engineering, product, and business teams.

Ideal candidates have a PhD in CS/ML/Statistics and a strong publication track in top venues. You will execute rigorous experiments, communicate complex ideas clearly, and contribute to end-to-end

Qualifications

• PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
• Strong foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
• Experience working with large-scale data and ML systems, through research or industry internships.
• Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• A track record of rigorous, high-quality research - publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
• Strong written and verbal communication skills - able to make complex ideas accessible across technical and non-technical audiences.

Responsibilities

• Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
• Develop user understanding systems - conversion prediction, behavioral modeling, and value estimation - that operate across billions of impressions.
• Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
• Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
• Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
• Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.
• You might also have industry experience in ads, recommendation, or user understanding systems (internship experience counts).
• Hands-on experience with production ML pipelines - training at scale, feature engineering, or experimentation infrastructure.
• Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
• Familiarity with agentic AI approaches - multi-step reasoning, tool use, or human-AI collaboration frameworks.
• Exposure to causal inference, uplift modeling, or A/B testing at scale.
• Genuine curiosity about applied research and the drive to see ideas through to impact.

Skills

Python

Reinforcement learning

LLM research

Publications

Communication

Education

PhD in CS/ML/Statistics

Tools

PyTorch

TensorFlow

Large-scale ML systems

Job description

The opportunity

Unity's Vector AI team builds the machine learning systems that decide which ads reach which players - across billions of monthly users on the world's leading game engine. Recommendation and ranking systems are the core of this work: predicting user value, optimizing bids, and delivering outcomes for advertisers at massive scale.

We are building the next generation of these systems. The frontier has shifted - large language models, reinforcement learning from human feedback, and agentic AI are reshaping what recommendation systems can do. We are looking for PhD graduates who have worked at that frontier and want to bring those ideas into production systems that matter.

What you'll be doing

• Design, build, and evaluate next-generation ranking and recommendation models that incorporate LLMs, RLHF, and preference learning to improve ad relevance and user experience.
• Develop user understanding systems - conversion prediction, behavioral modeling, and value estimation - that operate across billions of impressions.
• Apply reinforcement learning and optimization techniques to bidding strategy, auction dynamics, and real-time ad delivery.
• Design and run rigorous experiments using causal inference, A/B testing, and offline evaluation frameworks to measure and improve model quality.
• Partner with engineering to bring research ideas into production, working across the full pipeline from training data to deployed model.
• Communicate findings clearly to technical and non-technical stakeholders across engineering, product, and business teams.

What we're looking for

• PhD in Computer Science, Machine Learning, Statistics, or a related field (graduating 2026 or recent graduate).
• Strong research foundations in one or more of: recommendation systems, reinforcement learning, LLM post-training or alignment, human-AI collaboration, probabilistic modeling, or optimization.
• Experience working with large-scale data and ML systems, whether through research or industry internships.
• Fluency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• A track record of rigorous, high-quality research - publications at top venues (NeurIPS, ICML, ICLR, KDD, RecSys, ACL, WWW, or similar) are a strong signal.
• Strong written and verbal communication skills - able to make complex ideas accessible across technical and non-technical audiences.

You might also have

• Industry experience in ads, recommendation, or user understanding systems (internship experience counts).
• Hands-on experience with production ML pipelines - training at scale, feature engineering, or experimentation infrastructure.
• Experience applying LLMs or generative models to ranking, retrieval, or structured prediction problems.
• Familiarity with agentic AI approaches - multi-step reasoning, tool use, or human-AI collaboration frameworks.
• Exposure to causal inference, uplift modeling, or A/B testing at scale.
• Genuine curiosity about applied research and the drive to see ideas through to impact.

Additional information

• Relocation support is not available for this position

$127,400.00 - $191,200.00

_This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set._

Benefits

At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

• While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity

Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com .

_Unit