ML Engineer / Implementation Specialist

Binariks is looking for a detail-oriented and proactive Machine Learning Engineer to support experimental method development and integration within existing research codebases. This role requires strong implementation skills, comfort with low-level debugging, and the ability to communicate progress clearly.


What We’re Looking For:

• Strong coding skills, especially in research-oriented ML environments (e.g., PyTorch, JAX, TensorFlow).


• Ability to implement directly from formal or semi-formal method specifications.


• Experience working with varied data formats and integrating them into research pipelines.


• Familiarity with distributed training, benchmarking setups (e.g., RE-Bench or similar tools), and reproducibility best practices.


• Demonstrated technical contributions through public GitHub repositories or open-source work.


• Able to communicate technical progress and obstacles clearly to collaborators and stakeholders.
  
  
  

Your Responsibilities:

• Analyze and understand existing codebases to support seamless integration of new methods.


• Implement experimental methods based on provided specifications, ensuring correct loss function behavior and appropriate handling of model internals.


• Modify or extend existing logic and configurations as needed to support new research directions.


• Ensure experimental code is stable and reproducible, even at early stages of development.


• Provide timely progress updates via Loom or written summaries, including blockers and technical insights.