Jobs

Research Scientist Intern, Robotics Control Policy and Mechanics
Redmond, WA
·
On-site
·
Internship
·
2w ago
Compensation
$87,756 - $87,756
Benefits & Perks
•E Verify
Required Skills
Python
C++
Robotics
Reinforcement Learning
Imitation Learning
Kinematics
Rigid Body Dynamics
Solid Mechanics
At Reality Labs Research, our goal is to explore, innovate and design novel interfaces and hardware for the next generation of wearable experiences. We are driving research towards a vision of natural, seamless experiences in XR environments that are effective, enjoyable, and functionally indistinguishable from those in the real world.As a Research Scientist Intern, you will work at the intersection of robotic control, mechanics, and machine learning, and you will have the opportunity to work with world-leading collaborators and mentors in these fields. Your primary focus will be on developing novel robotic control policies for dexterous manipulation by combining data-driven approaches with mechanics.
Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Robotics Control Policy and Mechanics Responsibilities:
- Design and implement novel robotic control policies, leveraging both modern machine learning and physics-based modeling
- Conduct research on dexterous manipulation, specifically involving complex object interaction, uncertainty, and deformable bodies
- Develop and evaluate algorithms in both high-fidelity simulation and real-world robotic setups
- Collaborate with team members to integrate research insights into larger robotics platforms
- Prepare and present research findings for internal review and potential publication
Minimum Qualifications:
- Currently has or is in the process of obtaining a PhD in the field of Robotics, Mechanical Engineering, Computer Science, or a related technical field
- Demonstrated experience with modern machine learning-based control policies, such as Reinforcement Learning or Imitation Learning
- Understanding of classical robotics theory, including kinematics and rigid body dynamics
- Experience with solid mechanics and modeling for deformable bodies
- Proficiency in programming languages commonly used in robotics and machine learning (e.g., Python, C++)
- Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
- Intent to return to degree program after the completion of the internship/co-op
Preferred Qualifications:
- Experience with Robotics simulation environments (e.g., Mu JoCo, Isaac Gym, Py Bullet)
- Experience with open source solid mechanics simulation tools (e.g. Fenics, Deal-ii, Firedrake)
- Familiarity with deep learning frameworks (e.g., Py Torch, Tensor Flow)
- Experience with robotic hardware and real-world experimentation
- Experience working and communicating cross functionally in a team environment
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences
About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and Whats App further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$7,313/month to $12,134/month + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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About Meta

Meta
PublicA social technology company that enables people to connect, find communities, and grow businesses.
10,001+
Employees
Menlo Park
Headquarters
$800B
Valuation
Reviews
3.4
26 reviews
Work Life Balance
2.3
Compensation
4.2
Culture
2.8
Career
3.1
Management
2.1
45%
Recommend to a Friend
Pros
Excellent compensation and benefits
Smart and talented colleagues
Fast-paced and challenging work environment
Cons
Frequent layoffs and job insecurity
Poor leadership and management accountability
High stress and competitive work environment
Salary Ranges
40,175 data points
Mid/L4
Mid/L4 · Data Scientist
3,113 reports
$284,667
total / year
Base
$179,458
Stock
$79,981
Bonus
$25,228
$193,897
$434,902
Interview Experience
6 interviews
Difficulty
4.2
/ 5
Duration
21-35 weeks
Offer Rate
17%
Experience
Positive 17%
Neutral 17%
Negative 66%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Coding Interviews
6
System Design Interview
7
Behavioral Interview
8
Final Loop/Hiring Manager Round
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Live Coding
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