Machine Learning Engineer / Researcher

What you will do

• —Train, fine-tune, and evaluate models for on-device and cloud-based ML workloads.
• —Design and implement agent architectures that power Blackstar's intelligent features.
• —Build inference pipelines optimized for latency, memory, and power constraints.
• —Collaborate with software and hardware engineers to co-design systems that run efficiently on Blackstar devices.

What we are looking for

• —Strong understanding of modern ML architectures, including transformers, diffusion models, and RLHF.
• —Proficiency in Python and PyTorch; experience with model optimization tools (ONNX, TensorRT, Core ML, or similar).
• —Ability to read, implement, and adapt ideas from recent research papers.
• —You are based in or willing to relocate to San Francisco.

Nice to have

• —Experience with on-device ML, model compression, or edge inference.
• —Background in building agent systems or multi-step reasoning pipelines.

Compensation

$TBD + equity