Sr. Machine Learning Scientist, BioTalent, MA, US

Company Overview:

A cutting-edge biotechnology company using artificial intelligence to transform drug discovery is growing! Their proprietary AI platform decodes the complexity of genome biology to identify novel drug targets, mechanisms, and therapeutics that are inaccessible through traditional methods. Co-develop drug programs and AI models both internally and with partners, while also pursuing major technology builds alongside pharmaceutical collaborators. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, this multidisciplinary team is shaping the future of how new medicines are created.

Role Overview:

We are seeking an exceptional and creative Senior Machine Learning Scientist to join our core AI research team. You will pioneer novel deep learning systems to tackle fundamental research questions at the intersection of AI and biology. Working with domain experts, you will apply your ML expertise to unique, large-scale, and complex biological datasets, developing models that push the state-of-the-art. If you are a first-principles thinker excited to apply advanced ML skills to high-impact problems in human biology, health, and drug discovery, this is a unique opportunity.

Key Responsibilities:

• Lead the research and development of novel deep learning architectures, training paradigms (supervised, self-supervised, generative, multi-modal), and algorithms for large-scale biological sequence data and related modalities.
• Partner with computational biologists to integrate domain expertise, define scientifically meaningful tasks, and apply cutting-edge ML/AI research toward ambitious biological challenges.
• Implement, train, debug, and evaluate models rigorously to demonstrate scientific validity and drive progress in frontier health problems.
• Stay current with advancements in ML research and identify cross-disciplinary applications.
• Mentor junior scientists and engineers, fostering a culture of technical excellence and curiosity.
• Share research findings internally and contribute to the scientific community via publications in top-tier venues.

Basic Qualifications

• PhD (or equivalent expertise) in Machine Learning, Computer Science, Statistics, Physics, or related quantitative field.
• Deep understanding of modern deep learning methods, including Transformers, sequence models (e.g., state-space models), and LLMs.
• Strong ability to implement and debug high-performance ML models using frameworks like PyTorch or JAX.
• Proven record of solving complex, open-ended problems from conception to impactful solutions.
• Experience working with large datasets and at scale.
• Strong communication skills, able to collaborate with diverse technical and scientific teams.
• Track record of impactful research demonstrated through publications at top-tier ML conferences (NeurIPS, ICML, ICLR) or high-impact journals.
• 2+ years of post-graduate experience in a leading industrial R&D lab or highly competitive academic environment.
• Experience technically leading projects or mentoring junior researchers.
• Proficiency with cloud computing platforms (e.g., GCP) for large-scale training.
• Contributions to open-source projects that showcase problem-solving in ML.