Senior/Staff Software Engineer, ML Inference Platform

Mountain ViewOnsiteFull TimeStaffPosted 2 months ago

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Required skills

ML Infrastructure
ML model life cycle
model & data pipelines
optimized models
self-driving robots
ML workflow pipelines
model optimization
model validation
model deployment
continuous testing

Nice to have

C++
high-performance low-level languages
large-scale distributed systems
system & framework design
data workflow orchestration platforms
ML compilers

Role summary

Nuro is seeking a Senior/Staff Software Engineer for its ML Inference Platform team. This role involves designing, building, and deploying core infrastructure for machine learning model lifecycles, focusing on autonomy teams. Responsibilities include developing ML workflow pipelines, continuous testing and monitoring systems, and maintaining ML inference and compiler platforms. The ideal candidate has 3+ years of experience, strong Python skills, and experience with ML pipelines and distributed systems. Familiarity with C++ and ML compilers is a plus. This is a hybrid role with a competitive salary range and benefits.

Who We Are

Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides.Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles.With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected.Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors.

About the Role

The ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model & data pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots!

About the Work

Design and develop ML workflow pipelines to train, optimize, validate, and deploy Nuro autonomy models.

Develop and maintain continuous testing and monitoring systems for core ML infrastructure components.

Develop observability to track ML model lifecycles from data generation to on-road validation.

Maintain an in-house ML inference platform to serve large language models efficiently.

Maintain an in-house ML compiler platform to compile, deploy, and validate Nuro autonomy models to various hardware platforms.

About You

You have a degree in BS, MS.c or Ph.D and 3+ years of relevant experience

Strong proficiency in Python or similar languages. Familiarity with c++.

Technical excellence: Develop with a high standard for performance, scalability, and code quality.Domain experience: Experience working with ML pipelines; ability to understand and design complex distributed systems

Independence and productivity: Ability and willingness to dive into unfamiliar territory, learn fast, and improve complex systems.

Bonus Points:

Strong proficiency in C++ or other high-performance low-level languages

Experience working with large-scale distributed systems

Experience with system & framework design

Experience with data workflow orchestration platforms

Experience with ML compilers

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $352,290 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics.

Sample Nuro interview questions

1
Build a service discovery mechanism for distributed systems.
system designmedium
2
Maximum Depth of an N-ary Tree Find the maximum depth of an N-ary tree. Input: root = [1,null,2,null,3,null,4] Output: 4 Explanation: The tree is essentially a straight line, requiring a traversal that reaches a maximum depth of 4 layers.
codingmedium
3
Merge Overlapping Intervals Merge overlapping intervals in an array. Input: intervals = [[1,4],[4,5]] Output: [[1,5]] Explanation: The intervals touch exactly at the 4 mark, so they are successfully merged into a single continuous interval.
codingmedium
4
Lowest Common Ancestor on an N-ary Tree Find the lowest common ancestor on an N-ary tree. Input: root = [1,null,2,3,4], p = 2, q = 3 Output: 1 Explanation: Both nodes 2 and 3 are direct children of the root node 1, making 1 the lowest common ancestor.
codingmedium
5
Split Array into Consecutive Subsequences Split an array into consecutive subsequences. Input: nums = [1,2,3,4,4,5] Output: FALSE Explanation: The numbers can form [1,2,3,4], but the remaining leftover group [4,5] is too short to form a valid sequence of length 3.
codingmedium

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