Machine Learning Engineer – Intern

Our Mission Our mission is to tackle the most significant and foundational challenges in AI and Robotics, paving the way for future generations of intelligent machines that enhance our quality of life.
Internship Overview As a Machine Learning Engineering Intern, you will be part of a dynamic team, working cross-functionally to create groundbreaking technology to enhance the development and deployment of robotic systems. This opportunity is perfect for those who are passionate about pushing the boundaries of robotic capabilities through advanced technology. Located in our innovative Cambridge, MA office, we offer an on-site internship where you will contribute to building a collaborative and forward-thinking organization.

What You Will Do:

• Train, deploy, and maintain ML algorithms on both cloud and on-premise infrastructure, with a focus on modern ML practices including the use of DNNs, GNNs, Transformers, Diffusion models and Reinforcement Learning
• Develop and refine processes, pipelines, and tools covering all aspects of the ML lifecycle, from training and evaluation to deployment, utilizing frameworks like PyTorch Lightning and Ray
• Contribute to the construction and maintenance of data, model, and experimentation pipelines, assisting with model tuning, algorithm selection, and hyperparameter optimization through our MLOps platform
• Collaborate closely with research and applied science teams to transition models from conception to production
• Ensure code quality and reliability through regular code reviews and adherence to best software engineering practices

What You Will Need:

• Currently pursuing a BS or MS in Computer Science, Engineering, Data Science, or a related technical, mathematical, or scientific field
• Demonstrable experience with Python
• Knowledge of deep-learning techniques in NLP and Computer Vision, with a keen interest in transformers, diffusion models or reinforcement learning
• Proficiency in data science tools, libraries, and frameworks (e.g., NumPy, TensorFlow, PyTorch, Jax)
• Familiarity with git, issue tracking, CI/CD, and modern software development methodologies

Bonus Point for:

• Exposure to Docker, Kubernetes, cloud computing, or similar technologies
• Experience with data processing, logging, and visualization tools
• Familiarity with robotics simulation tools such as Isaac-sim or Mujoco and experience in simulation with learning workflows
• Understanding of MLOps practices, including model versioning, lineage, monitoring, deployment, scalability, orchestration, and continuous learning, with specific knowledge in tools like Airflow, Kubeflow, AWS Step Functions, and WandB
• Familiarity with DevOps practices, such as CI/CD Pipelines, Infrastructure as Code, and Agile software development methodologies
• Insight into edge computing, and big data processing (e.g., Hadoop, Spark, Presto, Kafka)

What You Will Gain:

• Hands-on experience implementing and scaling state-of-the-art ML models for robotics
• Insight into developing high-performance training systems that integrate with multi-modal data pipelines
• A collaborative and innovative environment that encourages rapid iteration and creative problem-solving
• Opportunity to contribute directly to the advancement of robotic capabilities, pushing the limits of what’s possible in AI

We are committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.