NLP/ML Engineer

Insilico Medicine

Responsibilities:

• Fine-tune and optimize Large Language Models on domain-specific or custom datasets.
• Analyze errors, identify system limitations, and propose enhancements.
• Search and review state-of-the-art solutions and new datasets for NLP tasks.
• Design scalable and maintainable engineering solutions inspired by the latest research and innovation.
• Translate academic innovation into scalable, maintainable engineering solutions.
• Build and curate datasets using annotation tools, distant supervision, and expert annotations.
• Collaborate closely with clients and internal stakeholders to align research-driven initiatives with business needs.

General Requirements:

I. Education

II. Experience and Skills

• 3+ years of hands-on experience in NLP, Machine Learning, and Deep Learning.
• Strong understanding of Machine Learning, Deep Learning and AI.
• Strong proficiency in Python programming.
• Motivation to learn new things and apply creative solutions.
• Hands-on experience in scaling and optimizing large language model (LLM) training and fine-tuning, including multi-GPU/multi-node setups.
• Familiarity with frameworks like DeepSpeed, FSDP, Megatron-LM, or equivalent.
• Ability to diagnose and resolve performance bottlenecks in distributed training.
• Experience fine-tuning LLMs (e.g. GPT, LLaMA, Mistral) on custom or domain-specific datasets.

Desirable skills:

• Knowledge of chemistry and biology, particularly for domain-specific NLP applications in life sciences.
• Familiarity with Reinforcement Learning concepts and frameworks.

Personal Attributes:

• Motivation to explore and apply creative, cutting-edge solutions.
• Strong communication and collaboration skills.
• Ability to work independently in a dynamic, fast-paced environment.