Job Details

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Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Position Overview
We are seeking a Machine Learning Engineer responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing models for real-world robotic environments. This role involves close collaboration with our robotics, research, and engineering teams. Your work will directly impact the development of intelligent, adaptable robots capable of autonomous learning and complex task execution.

Responsibilities

1. Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
2. Design and conduct experiments to train RL models and perform real-world testing.
3. Collaborate with researchers to explore methods for scaling RL model training.
4. Work with inference, application, and deployment engineers to integrate RL models into robotic systems and improve deployment robustness.
5. Analyze experimental results and iterate on model design for optimal performance.
6. Stay updated with the latest research and advancements in reinforcement learning.

Preferred Qualifications

• BS, MS, or higher in Computer Science, Robotics, Engineering, or a related field, or equivalent practical experience.
• Proficiency in Python, C++, or similar languages, and experience with deep learning libraries like PyTorch, TensorFlow, or JAX.
• Deep understanding of reinforcement learning algorithms (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
• Strong background in algorithms, data structures, and software engineering principles.
• Experience with physics simulation engines for training RL.
• Deep knowledge of state-of-the-art machine learning techniques and models.
• Industry experience with reinforcement learning and robotic systems is a plus.

Base Salary Range: $100,000 - $300,000 USD

Seniority level

• Entry level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Software Development

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Location and Salary Details

San Francisco, CA: $170,000.00-$250,000.00 (posted 20 hours ago)

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