Edge ML Engineer for Autonomous Construction Robots
Built Robotics Inc
San Francisco (CA)
On-site
USD 140,000 - 185,000
Full time
14 days+
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Benefits offered by this job
Competitive salary and equity
100% employer-sponsored health, dental and vision insurance
401(k) with employer matching
Paid holidays and flexible PTO
Gym membership
Free catered lunch and snacks
TSA PreCheck
A pair of steel-toe boots
Job summary
Built Robotics Inc is seeking a Machine Learning Engineer in San Francisco to design and develop machine learning systems for construction robots. The role requires a BS, MS, or PhD in relevant fields and over 3 years of experience with Python and ML frameworks. The position offers a competitive salary ranging from $140,000 to $185,000, equity, and comprehensive health benefits, including catered lunch, gym membership, and flexible PTO.
Qualifications
3+ years of experience building and deploying machine learning systems.
Expertise in Python and ML frameworks like PyTorch or TensorFlow.
Experience building distributed ML training systems and data pipelines.
Responsibilities
Design and develop edge machine learning systems for construction robots.
Build scalable ML infrastructure for model training, validation, and deployment.
Analyze large-scale operational datasets to improve model performance.
Skills
Machine learning systems development
Python programming
Experience with ML frameworks like PyTorch or TensorFlow
Distributed ML training systems
Robotics or autonomous systems experience
Education
BS, MS, or PhD in computer science, AI, machine learning, robotics or related field
Job description
Built Robotics Inc is seeking a Machine Learning Engineer in San Francisco to design and develop machine learning systems for construction robots. The role requires a BS, MS, or PhD in relevant fields and over 3 years of experience with Python and ML frameworks. The position offers a competitive salary ranging from $140,000 to $185,000, equity, and comprehensive health benefits, including catered lunch, gym membership, and flexible PTO.