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InternВ офисеКонтракт

Robot Learning Engineering Intern

Оценка ИИ

Исключительная возможность поработать с передовыми гуманоидными роботами в одной из ведущих компаний отрасли. Высокая оценка за инновационность задач и отличный социальный пакет даже для интернов.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью глубоких знаний в области робототехники (LfD, RL) и статуса студента магистратуры или аспирантуры. Работа предполагает интеграцию сложного ПО с реальным оборудованием, что требует высокой квалификации.

Анализ зарплаты

Медиана85 000 $
Рынок70 000 $ – 100 000 $
Оценка ИИ

Указанная ставка в $55 в час является очень конкурентоспособной для позиции интерна в области робототехники в США, соответствуя верхнему уровню рыночных ожиданий для студентов магистратуры и PhD.

Сопроводительное письмо

I am writing to express my strong interest in the Robot Learning Engineering Intern position at Agility Robotics. As a graduate student specializing in robotics and machine learning, I have followed Agility's progress in deploying humanoid robots with great admiration. My academic background and hands-on experience with robot manipulation and imitation learning align perfectly with the Skills team's mission to develop sophisticated learned behaviors for Digit.

During my studies, I have developed a solid foundation in Python and worked extensively with Learning from Demonstration (LfD) frameworks. I am particularly excited about the opportunity to work on force-aware and contact-rich manipulation tasks, as I believe these are critical for the next generation of autonomous systems. My experience in evaluating algorithms on real hardware has taught me the importance of robust data collection and rigorous experimental analysis, skills I am eager to apply to your robot learning testbeds.

I am confident that my technical skills and passion for embodied AI will allow me to make meaningful contributions to Agility Robotics. I look forward to the possibility of discussing how my background in robotics and machine learning can support your team's innovative work in Pittsburgh.

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Откликнитесь в agilityrobotics уже сейчас

Присоединяйтесь к команде Agility Robotics и создавайте будущее гуманоидных роботов уже сегодня!

Описание вакансии

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.

About the Role

We are looking for a graduate-level Robot Learning Engineering Intern to join our Skills team and support the development of learned manipulation behaviors for our humanoid robots. You will work at the intersection of robot learning, teleoperation, data collection, and on-robot evaluation, helping the team build and validate learning workflows that can support future deployment on humanoid systems.

This internship is especially well-suited for a graduate student who wants hands-on experience with a self-contained robot learning testbed and is excited to explore how high-quality demonstrations, sensing, and evaluation can be used to develop force-aware or contact-rich manipulation policies. You will work closely with engineers developing Learning from Demonstration (LfD) systems and learned robot skills, contributing to the tooling, experiments, and analysis needed to make these approaches useful in practice.

Key Responsibilities

  • Support demonstration data collection for learned robot behaviors using teleoperation and other operator-in-the-loop systems
  • Help build and improve a robot learning testbed, including integration of teleop interfaces, cameras, and other sensing required for data collection and evaluation
  • Assist with experiments focused on contact-rich or force-aware manipulation behaviors
  • Build and improve tooling for data ingestion, annotation, validation, replay, and analysis
  • Assist in evaluating learned policies in simulation and on real robot hardware
  • Partner with engineers to debug failures and improve system robustness
  • Analyze experiments and generate insights around data quality, policy behavior, and deployment readiness
  • Contribute to internal tools and infrastructure for robot learning development
  • Document findings and communicate results to mentors and cross-functional stakeholders

About You

  • Currently pursuing an MS or PhD in Robotics, Computer Science, Machine Learning, or a related field
  • Strong software engineering fundamentals and proficiency in Python
  • Background in robotics, machine learning, embodied AI, controls, or autonomous systems
  • Familiarity with at least some of the following: imitation learning, reinforcement learning, robot manipulation, force control, teleoperation, robot sensors, or object perception
  • Strong analytical, experimental, and debugging skills
  • Comfortable working hands-on with robotic systems in a lab environment

Bonus Qualifications

  • Experience with behavior cloning, Learning from Demonstration, offline RL, or learned control policies
  • Experience with robot data collection systems, VR/XR tools, haptics, or teleoperation interfaces
  • Experience with force/torque sensing or contact-rich manipulation tasks
  • Experience evaluating algorithms on real hardware rather than simulation alone

This is an onsite internship at our office in Pittsburgh, PA - minimum 4 days/week onsite.

Duration: Internship (3-6+ months, flexible)

Anticipated Base Salary Range

$55—$55 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 10 company holidays, including a winter shutdown.

+ Non-Exempt Employees: 10 vacation days, paid sick leave, and 10 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.

Apply Now: https://grnh.se/b444bbd04us

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Навыки

  • Python
  • Machine Learning
  • Computer Vision
  • Robotics
  • Control Theory
  • Reinforcement Learning
  • Imitation Learning
  • Robot Manipulation

Возможные вопросы на собеседовании

Проверка понимания фундаментальных концепций обучения роботов на основе демонстраций.

Каковы основные проблемы при использовании Imitation Learning для задач манипуляции с учетом силы (force-aware), и как бы вы их решали?

Оценка практического опыта работы с оборудованием и понимания разрыва между симуляцией и реальностью.

Расскажите о вашем опыте переноса алгоритмов из симуляции на реальное железо. С какими неожиданными трудностями вы столкнулись?

Проверка навыков работы с данными, что критично для этой роли.

Как вы оцениваете качество собранных данных телеоперации перед тем, как использовать их для обучения модели?

Оценка владения инструментарием и библиотеками для машинного обучения.

Какие библиотеки Python вы предпочитаете использовать для разработки RL-агентов или систем компьютерного зрения и почему?

Проверка навыков отладки сложных систем.

Опишите процесс отладки, когда робот ведет себя непредсказуемо при выполнении обученного навыка. С чего вы начнете поиск проблемы?

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Страна
США
Зарплата
55 $