Uber
From Uber's careers page
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The models making headlines are only as good as the data and feedback they learn from, and that is the work we do.
Uber AI Solutions (UAIS) is a startup inside Uber, building the data and evaluation infrastructure behind the next generation of AI. The models making headlines are only as good as the data and feedback they learn from, and that is the work we do.
We are an agile team moving at startup speed with the full weight of Uber behind us: global reach, world class infrastructure, and one of the largest human networks in the world. We pair that network with machine learning to produce the high quality, model ready data that the most advanced AI teams on earth depend on. Our work spans every modality, from text, images, and video to audio and physical AI and AVs, and reaches across dozens of countries.
This is a place for builders who want real ownership. Here you own a problem, not a ticket: you take a vertical from start to finish, the machine learning, the backend systems, and the product, and drive it from a blank page to something the best customers in AI rely on every day. You work shoulder to shoulder with product managers and other exceptional engineers, go as deep as the problem demands, and make the calls that decide whether your area wins. It is the closest thing to running your own company, with a rocket strapped to it.
If you want your work to show up in the AI systems shaping the world, and you want to build it like a founder, this is the team.
Build the ML and backend systems that turn your vision into a product customers pay for and rely on, going as deep as the problem requires.
Own your vertical end to end: find the opportunities, set the direction, and drive the business metrics that matter, such as revenue, adoption, and customer value.
Move fast in ambiguity: prioritize ruthlessly, make the calls, and turn ideas into shipped, revenue generating products with a product manager and a small senior team.
Be a trusted technical partner in the customer relationship where relevant, using what you learn to grow the account.
Raise the bar on execution and quality so your business can scale.
Bachelor's or equivalent work experience in Computer Science, Machine Learning, Engineering, Mathematics, or a related discipline.
5+ years of professional experience designing, building, and operating production ML systems, including strong backend engineering across the full path from data to serving.
Track record of driving business impact, not just shipping features: you have owned a product or product line and helped move metrics such as revenue, adoption, or customer value.
Fluency in Python for machine learning and a production systems language such as Go, Java, or C++, and the ability to build reliable services and run them in production.
Comfort operating in ambiguity and moving fast: you find the highest value problems yourself, make the call, and drive them without waiting to be told.
Excellent communication skills, with the ability to align customers, product, and engineering around what will grow the business.
Master's or PhD in Computer Science, Machine Learning, Engineering, Mathematics, or a related discipline.
You have grown a product or business line in a startup or startup like environment, owning outcomes end to end and treating revenue and customer growth as your job.
Experience applying machine learning to a real world data or evaluation domain, such as physical world data collection, RL environments and agentic evaluation, multilingual or audio data, or data quality and verification, where success was measured by business impact rather than model metrics alone.
Direct experience with GenAI and LLM systems in production, including evaluation harnesses, model tuning, forced alignment or ASR, or pipelines that keep a model in the loop.
Depth in one or more UAIS domains: real world and physical world data such as POI and embodied capture, agentic RL environments, multilingual and multimodal ML, video and LiDAR annotation, or physical AI and robotics data.
For San Francisco, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $232,000 per year - USD $258,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.
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Hi [Name], I just applied for the Staff Machine Learning Engineer - Uber AI Solutions role at Uber. My background in [your most relevant experience] lines up well with what the team is looking for. Would you be open to a quick chat, or could you point me to the right person on the team? Thank you!
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