Senior AI Engineer - Reinforcement Learning
Zurich
Software /
Full-Time /
On-site
Swiss-Mile Robotics AG is a deep-tech startup dedicated to delivering cutting-edge solutions for monitoring, security and logistics. We stand at the forefront of revolutionizing labor-intensive processes by connecting artificial intelligence with the physical world through autonomous robots.
We are seeking highly motivated, self-driven individuals with expertise in deep reinforcement learning (deep RL) and deep learning, including supervised and self-supervised learning. Become a valuable member of our innovative team, recognized for its innovation in deploying neural networks on actual robotic machines to enhance locomotion, navigation, and manipulation skills. With a rich research history at ETH Zurich, marked by state-of-the-art publications, we are pushing the boundaries of artificial intelligence in the real world. We are seeking a Senior AI Engineer with extensive experience in reinforcement learning and (self-)supervised learning to spearhead the expansion of our engineering team. As we tackle real-world challenges, your leadership will be crucial in harnessing the power of both simulated and real-world data. If you're passionate about advancing the field of AI and ready to contribute to groundbreaking solutions, join us in shaping the future of intelligent robotics.
Responsibilities
- Lead and mentor a team of engineers in developing and implementing reinforcement learning and (self-)supervised learning solutions for real-world robotics applications.
- Contribute to the design, optimization, and deployment of neural networks on physical robotics platforms to enhance locomotion, navigation, and manipulation capabilities.
- Collaborate with cross-functional teams to integrate AI solutions into robotics systems, ensuring seamless functionality and performance.
- Tailor and refine algorithms to align with the specific needs and requirements of clients, ensuring the successful integration of AI solutions into real-world use cases.
- Stay up-to-date of the latest advancements in reinforcement learning and deep learning, incorporating cutting-edge techniques into the development process.
- Utilize a combination of simulated and real-world data to train neural networks, actively engaging in the iterative refinement of algorithms to achieve higher performance and reliability.
- Provide technical expertise to guide strategic decision-making and project planning.
- Contribute to the development of documentation, guidelines, and best practices to ensure effective knowledge transfer within the engineering team.
- Actively participate in code reviews and contribute to the continuous improvement of coding standards and development processes.
Qualifications
- Bachelor's degree or higher in a relevant field, including but not limited to engineering, robotics, or machine learning.
- A minimum of 3+ years of industry or research experience, demonstrating a strong foundation in practical applications, demonstrating a track record of successful AI developments.
- Deep technical expertise in reinforcement learning (RL), encompassing Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc.
- Proficiency in both supervised and self-supervised learning techniques, showcasing a comprehensive understanding of diverse learning paradigms.
- Strong leadership and team management skills, with the ability to motivate and inspire engineering teams.
- Excellent analytical capabilities.
- Strong communication skills, encompassing written and verbal, and visual mediums, to articulate ideas clearly.
Bonus
- Experience in the robotics industry.
- Master's degree and PhD.
- Experience in managing a software team.
In your application, please share your previous successes in reinforcement learning and your strategy for growing a team of AI engineers.
We are looking forward to receive your application.
