ML Ops Developer Intern

There is energy here…energy you can feel crackling at any of our international locations. It’s an energy generated by enthusiasm for our work, for our teams, for our results, and for our customers. Lattice is a worldwide community of engineers, designers, and manufacturing operations specialists in partnership with world-class sales, marketing, and support teams, who are developing programmable logic solutions that are changing the industry. Our focus is on R&D, product innovation, and customer service, and to that focus, we bring total commitment and a keenly sharp competitive personality.

Energy feeds on energy. If you flourish in a fast paced, results-oriented environment, if you want to achieve individual success within a “team first” organization, and if you believe you can contribute and succeed in a demanding yet collegial atmosphere, then Lattice may well be just what you’re looking for.

As an ML Ops developer Intern, you will collaborate closely with both the DevOps and machine learning research teams to enhance our toolchain and workflow, thereby supporting model development and optimization. This position is well suited for individuals who are keen to gain hands-on experience in practical machine learning development.

Requirement

• Currently pursuing a degree in Computer Science, Computer Engineering, or a related field (minimum 2nd year).
• Basic understanding of machine learning concepts.
• Proficiency in Python, with the ability to write clean, maintainable code for both research and production environments.
• Strong problem-solving skills and a keen interest in practical machine learning applications.
• Solid experience with version control systems such as Git.

Nice to haves

• Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar platforms.
• Understanding of MLOps principles, including CI/CD pipelines, automation, and model lifecycle management.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform for deploying and scaling ML solutions.
• We would love to see any software development projects and code you have worked on.