Requirements

• Bachelor’s degree or equivalent practical experience.
• 2 years of software development or ML research experience, or equivalent education credit (e.g., internships, student research, pre-graduate experience).
• Experience conducting research to solve problems in AI or ML.
• Experience implementing machine learning algorithms or techniques (e.g., basic automatic differentiation) and using ML frameworks like Jax, PyTorch, Triton.
• Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
• One or more scientific publication submissions in conferences, journals, or public repositories, including on machine learning or computational neuroscience.

Nice to Haves

• Experience with distributed storage systems, relational databases, and schema or query design (e.g., PostgreSQL, Cloud Spanner, Bigtable, Cassandra, DynamoDB).
• Experience with large-scale data pipelines and distributed batch or streaming frameworks (e.g., Apache Beam, Spark, Dataflow, Ray, Flink).
• Prior experience building data infrastructure, pipelines, or tooling within an ML research environment.
• Familiarity with compiled systems/backend languages such as C++, Rust, Go, or Java, or media codecs (video, audio, image).

What You'll Be Doing

• Write product or system development code.
• Review code from other developers, providing feedback on best practices such as style guidelines, accuracy, testability, and efficiency.
• Participate in or lead design reviews with peers and stakeholders to select appropriate technologies.
• Triage product or system issues by analyzing causes and impacts on hardware, network, or service operations and quality, then debug and resolve them.
• Contribute to and adapt documentation or educational content based on product updates and user feedback.