AI & ML Engineer

Built Robotics Inc; San Francisco (CA); On-site; USD 140,000 - 185,000; Full time

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

WHO WE ARE

Built Robotics’ mission is to build the robots that build the world. By automating repetitive tasks in the $300 billion solar industry, Built is bridging the workforce gap to accelerate our transition to clean energy.

WHAT YOU’LL DO

• Design and develop edge machine learning systems that to improve the autonomy and safety of our construction robots
• Build scalable ML infrastructure for model training, validation, deployment, and monitoring
• Develop and optimize computer vision and sensor fusion models for construction environments
• Analyze large-scale operational datasets to improve model performance and reliability
• Improve object recognition, scene understanding, and autonomous decision-making systems
• Integrate cloud-based commercial and open-source AI tools into our autonomy stack

YOUR QUALIFICATIONS

• BS, MS, or PhD in computer science, artificial intelligence, machine learning, robotics, or related field
• 3+ years of experience building and deploying machine learning systems
• Expertise in Python and ML frameworks such as PyTorch or TensorFlow
• Experience building distributed ML training systems and data pipelines
• Robotics or autonomous systems experience is a plus

COMPANY PERKS

• Competitive salary and equity
• 100% employer-sponsored health, dental and vision insurance — for you, your spouse and children
• 401(k) with employer matching
• Paid holidays and flexible PTO
• TSA PreCheck
• Gym membership
• Free catered lunch and plenty of snacks
• A pair of steel-toe boots

ABOUT THE COMPANY & ROLE

The starting annual base salary range for this role is $140,000 to $185,000. Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications, working location, and market demands. The total compensation package for this role may also include: equity compensation, benefits such as medical, dental and vision insurance, 401(k) matching, paid time off, cell phone and internet reimbursement and more.

Built Robotics provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Built Robotics makes hiring decisions based solely on qualifications, merit, and business needs at the time.