Unity Logo

Unity

Machine Learning Engineer

Posted Yesterday
Hybrid
2 Locations
104K-152K Annually
Entry level
Hybrid
2 Locations
104K-152K Annually
Entry level
Build and maintain large-scale data pipelines and infrastructure for training data generation, distributed model training, and ML workflows. Support reproducibility, validation, monitoring, and performance optimization. Collaborate with ML engineers and researchers to productionize research and evolve the offline ML platform.
The summary above was generated by AI

The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.

We’re looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems.

You’ll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you’ll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient.

This role offers the opportunity to bridge research and production—translating advanced ideas into systems that operate at scale.

What you'll be doing

  • Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
  • Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
  • Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
  • Improve reproducibility and reliability through dataset validation, monitoring, and testing
  • Partner with ML engineers to support experimentation and model iteration
  • Help optimize performance and efficiency across data processing and training systems
  • Contribute to the evolution of our offline ML platform architecture as it scales

What we're looking for

  • Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field
  • Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
  • Experience with Python and working with data-intensive workloads
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
  • Experience (academic or applied) with data pipelines, model training workflows, or large datasets
  • Strong problem-solving skills and ability to translate research ideas into practical systems
  • Interest in building scalable, reliable infrastructure for machine learning
  • Nice to Have
  • Experience with workflow orchestration systems (Airflow, Flyte, etc.)
  • Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
  • Publications or research in ML systems, distributed systems, or related areas

Additional information

  • Relocation support is not available for this position
  • Work visa/immigration sponsorship is not available for this position

Base Salary Range: We determine the base salary range for this role based on your primary work location:

Mountain View, SF/Bay: $117,000 - $152,000 gross USD
Bellevue, Seattle, NYC, Remote CA: $104,100 - $135,300 gross USD

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. For more information, please visit www.unity.com.


Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.


Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.


This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.


Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.


Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at [email protected].

HQ

Unity San Francisco, California, USA Office

San Francisco, CA, United States

Unity San Francisco, California, USA Office

Work at Unity includes a ton of flexibility, depending on your role, the needs of your team and ultimately the way you and your team work best together.

Similar Jobs

5 Days Ago
Easy Apply
Hybrid
Easy Apply
90K-210K Annually
Mid level
90K-210K Annually
Mid level
Aerospace • Artificial Intelligence • Computer Vision • Machine Learning • Natural Language Processing • Software • Defense
Design, implement, and optimize computer-vision and multimodal ML algorithms; acquire and manage truth data; run experiments and rigorous evaluations; use MLOps tools for reproducibility; integrate and transition models to production (cloud, on‑prem, or embedded); track research advancements and analyze field-test data.
Top Skills: AimstackAirflowAWSAzureComputer VisionDockerLlmMlflowMlopsObject DetectionPythonTracking
7 Days Ago
Hybrid
149K-225K Hourly
Mid level
149K-225K Hourly
Mid level
eCommerce • Healthtech • Pet • Retail • Pharmaceutical
Design, train, and deploy ML and deep-learning models for sponsored ads: relevance, ranking, click-through prediction, auction and bidding optimization. Lead models from ideation through production, collaborate with product and engineering, set modeling standards, mentor junior scientists, and communicate results to leadership.
Top Skills: AWSAws SagemakerClassificationDeep LearningDistributed PipelinesGenerative AiLarge-Scale EmbeddingsLinear ProgrammingLlmsPersonalizeRankingRegressionSearchTime Series
8 Days Ago
Hybrid
Senior level
Senior level
eCommerce • Fintech • Real Estate • Software • PropTech
Design, build, and operate production ML models, services, and platforms for pricing, risk, and decision systems. Own end-to-end model pipelines, deployment, monitoring, and iteration. Collaborate with researchers and product to productionize prototypes, tackle data drift and sparsity, lead design reviews, and mentor teammates.
Top Skills: AirflowDelta LakeMlflowPythonSpark

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account