4 ΡΠ°ΡΠ° Π½Π°Π·Π°Π΄
Research Engineer, Post-training & Deployment (Robotics AI)
100Β 000 - 300Β 000$
ΠΡΡΡ & Π‘ΠΎΠΏΡΠΎΠ²ΠΎΠ΄
ΠΠ»Ρ ΠΌΡΡΡΠ° Ρ ΡΡΠΎΠΉ Π²Π°ΠΊΠ°Π½ΡΠΈΠ΅ΠΉ Π½ΡΠΆΠ΅Π½ Plus
ΠΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π²Π°ΠΊΠ°Π½ΡΠΈΠΈ
Π’Π΅ΠΊΡΡ:
TL;DR
Research Engineer, Post-training & Deployment (Robotics AI) (Python/Deep Learning/Robotics): Improving and deploying foundation models for robotic manipulation in real-world customer environments with an accent on post-training, robot behavior evaluation, and reliable field deployment. Focus on building continuous-improvement frameworks, managing deployment data and scenarios, and designing testing pipelines for model gains and corner cases.
Location: San Mateo, CA, United States
Base salary: $100,000β$300,000 USD per year
Company
develops general-purpose robotic intelligence that adapts to unseen scenarios and supports large-scale robot deployment.
What you will do
- Research, post-train, and evaluate large deep learning models for robotic manipulation.
- Develop frameworks for continuously improving robot behaviors.
- Collaborate with product teams to refine customer requirements for on-site deployments.
- Define scenario setup and data collection methods for customer use cases.
- Maintain deployment readiness and execute full-stack software and hardware deployments at customer sites.
- Build testing and evaluation pipelines to track model improvements and corner cases.
Requirements
- Degree in Computer Science, Robotics, Engineering, or a related field, or equivalent practical experience.
- Proficiency in Python and at least one deep learning library, such as PyTorch, TensorFlow, or JAX.
- Strong knowledge of computer vision and deep learning for robotics, including reinforcement and imitation learning.
- Experience with large-scale model training.
- Experience developing and deploying machine learning models or software on real robots.
- Experience with ROS, ROS2, or another robotics middleware platform.
Nice to have
- Experience working with customers and deploying real-world robotics applications.
- Experience using LLMs to accelerate development and solve complex engineering problems.
Culture & Benefits
- Work spans the transition from laboratory robotics performance to dependable customer deployments.
- Projects focus on safe, efficient, and robust robot behavior under operational constraints.
- Opportunities to work with colleagues ranging from new graduates to domain experts.
ΠΡΠ΄ΡΡΠ΅ ΠΎΡΡΠΎΡΠΎΠΆΠ½Ρ: Π΅ΡΠ»ΠΈ ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Ρ ΠΏΡΠΎΡΠΈΡ Π²ΠΎΠΉΡΠΈ Π² ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ, ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡ iCloud/Google, ΠΏΡΠΈΡΠ»Π°ΡΡ ΠΊΠΎΠ΄/ΠΏΠ°ΡΠΎΠ»Ρ, Π·Π°ΠΏΡΡΡΠΈΡΡ ΠΊΠΎΠ΄/ΠΠ, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡΠ΅ ΡΡΠΎΠ³ΠΎ - ΡΡΠΎ ΠΌΠΎΡΠ΅Π½Π½ΠΈΠΊΠΈ. ΠΠ±ΡΠ·Π°ΡΠ΅Π»ΡΠ½ΠΎ ΠΆΠΌΠΈΡΠ΅ "ΠΠΎΠΆΠ°Π»ΠΎΠ²Π°ΡΡΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡΠΈΡΠ΅ Π² ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β
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