Join Skild AI as a Machine Learning Engineer to develop cutting-edge reinforcement learning algorithms for adaptable robotic systems.
Posted by employer 2 years ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
Requirements
- Education
- Bachelor's degree
Not disclosed in this posting: years of experience, work arrangement, visa sponsorship.
Joblaze summary
In this role, the Machine Learning Engineer focuses on designing and implementing advanced reinforcement learning algorithms to enhance robotic capabilities. Key skills include proficiency in Python or C++, experience with deep learning frameworks, and a solid understanding of various reinforcement learning techniques. This position is ideal for individuals with a strong background in machine learning and robotics, whether they are seasoned professionals or recent graduates eager to innovate. Skild AI fosters a collaborative environment, encouraging team members to explore new methodologies in robotic intelligence.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Skild AI's career page.
- Skild AI has 63 other open roles including Manufacturing Engineering Manager, Senior Electrical Engineer , Operations Program Manager – Data Infrastructure - India.
- 6527 active Python roles on Joblaze right now.
- 1661 active C++ roles on Joblaze right now.
- 481 active PyTorch roles on Joblaze right now.
- Salary band is below the typical range for AI/ML roles (median ~$188,000).
- Pays more than 8% of the 3228 salaried Python roles we track (median $160,000). See Python salary trends
Quick facts
- What's the salary range?
- Skild AI lists $100,000–$300,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, JAX, PyTorch, Python, Robotics, TensorFlow.
- What seniority level is this role?
- Skild AI targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Machine Learning Engineer, Reinforcement Learning role at Skild AI.
From the original posting
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 looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.
Responsibilities
- Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
- Design and conduct experiments to train RL models and conduct real-world tests.
- Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
- Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
- Analyze and interpret experimental results, iterating on model design to achieve desired performance.
- Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
- BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
- Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
- Deep understanding and practical experience with various reinforcement learning algorithms and techniques (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 and tools for training RL.
- Deep understanding of state-of-the-art machine learning techniques and models.
- Extensive industry experience with reinforcement learning and robotic systems.