Staff AI Engineer, Perception
Agility Robotics — Artificial Intelligence · Automation · Automotive
About the role
Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.
Agility Robotics is deploying humanoid robots that are solving real-world challenges in logistics and manufacturing. Perceiving and understanding the world is critical to Digit’s success in these applications. The Perception team is looking for a staff machine learning engineer to own the design and development of object detection and tracking algorithms.
Responsibilities:
As a technical lead, you will own the architecture and technical roadmap for object perception systems used by the robot in production
Design, develop, and deploy machine learning algorithms for multi-object detection, scene understanding, and 6-DoF object pose estimation
Evaluate and drive adoption of state-of-the-art perception models
Promote best practices in architecture, design, and testing to deliver high-quality, scalable software
Optimize deep neural networks and associated data processing to run efficiently on embedded systems
Collaborate with navigation, manipulation and hardware teams to align perception capabilities with product requirements
Requirements:
5+ years of experience deploying machine learning-based object detection algorithms on mobile robots with at least 2 years of experience in a technical leadership role
Master's or Ph.D. in Artificial Intelligence, Robotics, Computer Science, or a related discipline, with a strong foundation in machine learning, robotics, and intelligent systems
Proficiency in related technical areas such as (but not limited to) deep convolutional neural networks, multi-object tracking, data association, supervised learning and pose estimation
Strong mathematical fundamentals in linear algebra and numerical optimization and familiarity with core geometric concepts in computer vision
Familiarity with common computer vision and machine learning libraries such as (but not limited to) PyTorch, OpenCV, NumPy, etc.
Experience designing and optimizing algorithms for efficient execution across CPU and GPU architectures
Experience with MLOps such as (but not limited to) data annotation services, data storage, model evaluation tools, and model deployment
Publications in your field (CVPR, ICCV, RSS, ICRA preferred)
Bonus Qualifications:
Experience using YOLO, Faster/Mask R-CNN
Experience developing ML models for 3 or 6 dof pose estimation
This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.
The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.
Anticipated Salary Range
$207,000 $323,000 USD
In addition to base pay, our competitive total rewards package consists of the following for full-time employees:
401(k) Plan: Includes a 6% company match.
Equity: Company stock options.
Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
Benefit Start Date: Eligible for benefits on your first day of employment.
Well-Being Support: Employee Assistance Program (EAP).
Time Off:
Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.
Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
Parental Leave: Generous paid parental leave programs.
Work Environment: A culture that supports flexible work arrangements.
Growth Opportunities: Professional development and tuition reimbursement programs.
Relocation Assistance: Provided for eligible roles.
Annual Discretionary Bonus: Provided for eligible roles.
All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.
Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.
Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies. We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page. If you are represented by a third party, your application may not be considered. To ensure full consideration, please apply directly.
What the index says about this role
- First seen by JobLarper — Aug 2, 2026, 6 days ago. Older postings collect hundreds of applicants — a tailored résumé matters more the longer a role has been live.
- No pay range in our index for this listing. Across 193 indexed Machine Learning Engineer roles in US that do publish one, the middle half sits between $213k and $300k, median $250k — JobLarper's read of the market, not a figure from Agility Robotics.
- What Machine Learning Engineer roles ask for — across 1,108 indexed openings: ML (78%), AI/LLM (55%), Python (53%), REST/APIs (38%), Cloud (25%). This posting names ML.
- Agility Robotics is hiring actively — 32 open roles indexed.
Derived from the 27,000 roles JobLarper indexes daily from official company boards — not from the job description above.
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