PhD Machine Learning Software Engineer Intern (Summer 2027)

What you'll do

• Lead a research project from problem framing through method development, evaluation, and publication write-up.
• Design, build, train, and test ML models; turn prototypes into production-quality code and pipelines.
• Analyze data and communicate results while collaborating with product, data science, and engineering teams.

What they ask for

• Currently pursuing a PhD in a stated technical field, returning after the internship, with graduation between December 2027 and Summer 2028.
• Track record of ML research through publications, preprints, or substantial research projects.
• Strong foundation in reinforcement learning and sequential decision-making, and grounding in causal inference and counterfactual evaluation.
• Strong programming skills in Python or a similar language; ability to translate research papers into working code.

Nice to have

• Publications at venues such as NeurIPS, ICML, ICLR, KDD, WWW, RecSys, or AAAI.
• Experience with offline reinforcement learning, off-policy evaluation, logged interaction data, recommender systems, large-scale ML workflows, or online experimentation.

Pay

$65-$68/hour (base salary)

Tools

PyTorch, TensorFlow, JAX, Python, Spark, SQL

AI focus

Applied ML research involving reinforcement learning, sequential decision-making, personalization, and rigorous offline and online evaluation; target outcome includes a paper submission to a top ML venue.