Level

Agility RoboticsPosted 5mo ago

Staff AI Engineer, Perception

Staff AI Engineer, Perception at Agility Robotics scores 91 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Hybrid- Any Office (Fremont, CA, Salem, OR, or Pittsburgh, PA)lead$207k-$323k

AI in this role

pytorch
ml-opsai-evaluationai-data-labelingcomputer-vision

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 Staff AI Engineer, 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
  • 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
  • Experience in a technical leadership role

 

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.

 

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Skills and AI tools this role asks for

Ml OpsAI EvaluationAI Data LabelingComputer VisionPyTorch

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. How do you decide that one model's output is better than another's for a given task?
  3. How do you keep labeling instructions consistent across a large annotation team?
  4. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  5. Walk me through how you've used PyTorch in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Ml Ops, AI Evaluation, AI Data Labeling, Computer Vision, and PyTorch. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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