ML Engineer

The Role: ML Engineer - NLP Expertise for Biological and Genomic Data

Overview:
We are seeking a skilled ML Engineer with strong expertise in Natural Language Processing (NLP) to work on developing, fine-tuning, and deploying models focused on biological and genomic data. This role requires deep research, foundation models, and innovative architecture design—moving beyond off-the-shelf AI solutions.

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Key Responsibilities

• Design and Train Custom LLMs:

  • Develop specialized language models tailored for biological and genomic data.

• Implement Training Pipelines:

  • Build efficient training pipelines using PyTorch, Hugging Face, and distributed computing methods.

• Innovate in Model Architecture:

  • Create novel model architectures and push the limits of AI in genomics and life sciences.

• Collaborate with ML Researchers:

  • Work closely with ML researchers and domain experts to design high-impact AI solutions.

• Stay Updated:

  • Keep ahead of the latest advancements in AI research (e.g., LLMs, protein modeling, etc.).

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What We're Looking For

• 4+ years of hands-on experience in NLP & Deep Learning.
• Strong background in PyTorch.
• Experience training models from scratch and fine-tuning LLMs, not just using LangChain or API-based AI.
• Deep understanding of transformer architectures, tokenization, and self-supervised learning.
• Solid software engineering skills (writing clean, modular, and scalable ML code).
• Experience with distributed training (DDP, FSDP, multi-GPU scaling, etc.).
• Experience in bioinformatics, genomics, computational biology (advantage).