Machine Learning Engineer
Description For Machine Learning Engineer
The Boston Dynamics AI Institute is seeking a Machine Learning Engineer to join their team in Cambridge, MA. This role offers an exciting opportunity to work on cutting-edge AI and robotics challenges in a collaborative environment.
As a Machine Learning Engineer, you'll work cross-functionally to create new technology that improves machine learning pipelines for robots. Your responsibilities will include training, deploying, and maintaining ML models, developing pipelines for the entire ML lifecycle, and partnering with research and engineering teams on model architecture design and implementation.
The ideal candidate should have a strong background in computer science or engineering, with at least 6 years of experience in machine learning engineering or related fields. You should be proficient in Python or C++, have experience with cloud ecosystems like GCP and AWS, and be familiar with deep learning libraries such as PyTorch and TensorFlow.
This role offers the chance to work with state-of-the-art deep learning techniques in robotics, computer vision, and NLP. You'll contribute to a vibrant research environment, staying up-to-date with the latest innovations in ML architectures and their applications to robotics.
Join the Boston Dynamics AI Institute in their mission to solve fundamental AI and robotics challenges and help shape the future of intelligent machines. This on-site position in Cambridge, MA provides an excellent opportunity for growth and innovation in the exciting field of AI and robotics.
Responsibilities For Machine Learning Engineer
- Train, deploy, and maintain various ML models on cloud and on-premise infrastructure
- Develop pipelines and tools for all components of the ML lifecycle – from training, evaluation, and optimization to deployment
- Partner closely with research and engineering teams on model architecture design, implementation, experimentation, and productionalization
- Promote quality and reliability through regular code reviews
- Contribute to the vibrant research and learning environment of the Institute by staying up to date on the latest innovations in ML architectures, frameworks and applications to robotics
Requirements For Machine Learning Engineer
- BS or MS in computer science, engineering, or equivalent technical experience
- 6+ years overall experience (3+ post-Masters or PhD) as a machine learning engineer, software engineer, or applied scientist
- Experience writing production code for data processing, machine learning training, and/or serving in Python, C++, or similar
- Experience with git, issue tracking, CI/CD, and modern software engineering practices
- Experience with cloud ecosystems such as GCP and AWS
- Experience with deep learning libraries and frameworks such as PyTorch, TensorFlow and Flax
- Hands-on experience implementing and training deep learning models
- Experience with state-of-the-art deep-learning techniques such as transformers, diffusion models, and multi-modal modeling, in domains such as robotics, computer vision, and NLP
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