Machine Learning Engineer

• 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.

• 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.