EPM Scientific
Founding Machine Learning Engineer (San Francisco County)
EPM Scientific, San Francisco, California, United States, 94133
Founding Machine Learning Engineer
An early-stage
startup led by veterans from top AI labs
is using machine learning to unlock breakthroughs in RNA biology. This is an opportunity to join a team at the cutting edge of
AI-driven molecular design , where your work will directly accelerate the development of next-generation therapeutics and biological systems. As an early hire, you'll have significant ownership over the technical stack and play a key role in shaping the company's culture and trajectory. If you're excited by the idea of building scalable ML systems in a fast-moving, interdisciplinary environment, this role is for you.
Responsibilities Design and implement high-performance training pipelines for large-scale RNA models. Develop distributed training strategies across multi-GPU/TPU environments for maximum efficiency. Build robust data infrastructure for ingesting, cleaning, and managing complex biological datasets. Collaborate with research scientists to translate RNA-focused challenges into ML solutions. Contribute to model architecture design, fine-tuning strategies, and performance benchmarking. Establish best practices for reproducibility, testing, and deployment in ML workflows.
Qualifications
3+ years of experience in machine learning engineering or related roles. Strong programming skills in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow). Hands-on experience training large-scale models (transformers, diffusion, or similar). Expertise in distributed training, optimization, and performance profiling. Proven ability to deliver production-grade ML systems.
Preferred: Experience with biological or other high-dimensional scientific data. Background in computational biology, bioinformatics, or aligned fields.
An early-stage
startup led by veterans from top AI labs
is using machine learning to unlock breakthroughs in RNA biology. This is an opportunity to join a team at the cutting edge of
AI-driven molecular design , where your work will directly accelerate the development of next-generation therapeutics and biological systems. As an early hire, you'll have significant ownership over the technical stack and play a key role in shaping the company's culture and trajectory. If you're excited by the idea of building scalable ML systems in a fast-moving, interdisciplinary environment, this role is for you.
Responsibilities Design and implement high-performance training pipelines for large-scale RNA models. Develop distributed training strategies across multi-GPU/TPU environments for maximum efficiency. Build robust data infrastructure for ingesting, cleaning, and managing complex biological datasets. Collaborate with research scientists to translate RNA-focused challenges into ML solutions. Contribute to model architecture design, fine-tuning strategies, and performance benchmarking. Establish best practices for reproducibility, testing, and deployment in ML workflows.
Qualifications
3+ years of experience in machine learning engineering or related roles. Strong programming skills in Python and deep learning frameworks (PyTorch, JAX, or TensorFlow). Hands-on experience training large-scale models (transformers, diffusion, or similar). Expertise in distributed training, optimization, and performance profiling. Proven ability to deliver production-grade ML systems.
Preferred: Experience with biological or other high-dimensional scientific data. Background in computational biology, bioinformatics, or aligned fields.