EPM Scientific
We are looking for a Founding Machine Learning Engineer to lead the development of scalable ML systems for RNA biology at EPM Scientific.
Base Pay Range $220,000.00/yr – $260,000.00/yr
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
4+ 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.
Seniority Level Entry level
Employment Type Full-time
Job Function Research
Location:
San Francisco, CA
#J-18808-Ljbffr
Base Pay Range $220,000.00/yr – $260,000.00/yr
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
4+ 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.
Seniority Level Entry level
Employment Type Full-time
Job Function Research
Location:
San Francisco, CA
#J-18808-Ljbffr