Machine Learning Engineer (Platform)
Artera$140,000 - $180,000/year
Full Time
Junior (1 to 2 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Autonomous Driving, Robotics, AIIndustries
Requirements
- 4+ years of ML infrastructure experience
- Experience building large-scale distributed multi-node GPU model training and/or high throughput, low latency serving use cases
- Experience with training frameworks like PyTorch and OSS frameworks like Ray
- Experience with GPU-accelerated inference using TensorRT, Ray Serve, or a similar framework
- Experience working with cloud providers like AWS
Responsibilities
- Build the Zoox Training framework leveraged by all ML teams within Zoox. This framework needs to be highly scalable, reliable, and efficient
- Build the Off-vehicle inference service powering our Foundational models and the models that improve our rider experiences
- Lead the design, implementation, and operation of a robust and efficient ML platform to enable the training, validation, serving, and monitoring of ML models
- Collaborate closely with cross-functional teams, including ML researchers, software engineers, and data engineers, to define requirements and align on architectural decisions
- Enable the junior engineers in the team to grow their careers by providing technical guidance and mentorship
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What is the salary range for this Senior Software Engineer role?
The salary range is $220,000 to $285,000. Compensation also includes Amazon Restricted Stock Units (RSUs), Zoox Stock Appreciation Rights, and possibly a sign-on bonus, varying by geographic location and level.
Is this position remote or does it require working from an office?
This information is not specified in the job description.
What skills and experience are required for this role?
Candidates need 4+ years of ML infrastructure experience, expertise in large-scale distributed multi-node GPU model training or high throughput/low latency serving, experience with PyTorch and OSS frameworks like Ray, GPU-accelerated inference using TensorRT or Ray Serve, and working with cloud providers like AWS.
What is the team structure and culture like at Zoox's ML Platform team?
The ML Platform team collaborates across all ML teams at Zoox including Perception, Prediction, Planner, Simulation, Data Science, and Collision Avoidance, as well as Advanced Hardware Engineering. The role involves mentoring junior engineers to support career growth in a high-impact environment focused on scaling ML for autonomous driving.
What makes a strong candidate for this position?
Strong candidates have 4+ years of ML infrastructure experience, particularly in scalable GPU training or low-latency inference, proficiency with PyTorch, Ray, TensorRT, and AWS, plus the ability to lead platform design and collaborate cross-functionally.
Zoox
Develops autonomous electric ride-hailing vehicles
About Zoox
Zoox focuses on creating a fully integrated autonomous ride-hailing service designed specifically for urban transportation. Unlike other companies that modify existing vehicles for self-driving capabilities, Zoox has engineered its own vehicle from the ground up, optimizing it for safety, efficiency, and passenger comfort. The vehicle features advanced sensors, cameras, and AI systems that allow it to navigate complex city environments. It can carry up to four passengers in a spacious interior, ensuring a pleasant ride experience. Safety is paramount, with rigorous testing and collaboration with regulatory bodies to meet high standards. Additionally, Zoox's vehicles are fully electric, promoting sustainability by reducing emissions. The company also develops a user-friendly ride-hailing platform that uses data analytics to improve routing and reduce wait times. Zoox aims to enhance urban mobility while prioritizing safety and environmental responsibility.
Menlo Park, CaliforniaHeadquarters
2014Year Founded
$1,206.2MTotal Funding
ACQUISITIONCompany Stage
Automotive & Transportation, Energy, AI & Machine LearningIndustries
1,001-5,000Employees
Benefits
Health Insurance
Maternity & Paternity Leave
Vacation & Paid Time Off
Sick Days
Free Lunch or Snacks
Employee Assitance Program
Risks
Increased competition from Waymo and Cruise may impact Zoox's market share.
Expansion into new cities introduces regulatory and operational challenges for Zoox.
Partnership with Williams Racing may divert focus from core vehicle development.
Differentiation
Zoox designs vehicles specifically for autonomous operation, unlike retrofitting existing cars.
Zoox's vehicles feature a unique, futuristic design with advanced AI systems.
Zoox offers a fully integrated ride-hailing service optimized for safety and efficiency.
Upsides
Zoox's expansion into Austin and Miami opens new markets and data collection opportunities.
Partnership with Williams Racing boosts Zoox's brand visibility in the U.S. market.
Hiring former Tesla executive Gao could accelerate Zoox's technological advancements.
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