Machine Learning Researcher / Engineer — Deep Learning for Molecular Simulation and Drug Discovery
The Opportunity
Changing how new medicines are found depends on understanding proteins and related biological macromolecules at the molecular level, and on simulating their behavior far faster than conventional methods allow. Machine learning is a growing part of that effort. Current work ranges from neural networks that sharpen the accuracy of quantum chemistry models to deep generative models that design molecules optimized as drug candidates. In this role, you will extend that work by building deep learning methods that advance biophysics, biomolecular simulation, and drug discovery.
The company is an independent research group based in New York City. Its central focus is molecular simulation, and its long-range aim is to change how drugs are discovered.
The Research Environment
Machine learning researchers at the client work alongside chemists, biologists, and computer scientists on a single interdisciplinary team. They draw on several generations of special-purpose, large-scale computing infrastructure built to accelerate molecular dynamics by orders of magnitude. They also use in-house software designed to push forward the state of biochemistry and molecular biology.
What You’ll Do
- Develop new deep learning techniques aimed at open problems in biomolecular simulation, biophysics, and drug discovery.
- Extend the group’s existing neural network models that raise the accuracy of quantum chemistry calculations.
- Refine generative approaches that propose molecules optimized for drug discovery.
- Partner with chemists, biologists, and computer scientists to identify where machine learning can broaden the group’s research.
- Translate methodological advances into software tools that support simulation of proteins and other macromolecules.
What You Bring
- Demonstrated expertise in developing Deep Learning techniques
- Strong command of Python programming
- Notable academic and professional accomplishments, including evidence of innovation in Machine Learning
- Intellectual curiosity and the versatility to move across scientific domains
- Background in one or more of Quantum Chemistry, Cheminformatics, Medicinal Chemistry, Structural Biology, or Molecular Dynamics. This background is relevant, but the client weighs it below the qualities listed above.
- Commitment to a stimulating, positive, and collaborative workplace
Paths Into This Role
This role suits candidates whose research training centered on building and advancing deep learning methods. That includes work in computer science and machine learning, and work in computational fields such as quantum chemistry, cheminformatics, molecular dynamics, structural biology, or medicinal chemistry where learned models played a central role. Domain depth in the life sciences helps. The client places greater weight on a proven record of machine learning innovation.
Compensation & Total Rewards
- Expected annual base salary of $300,000–$900,000. The client sets the final figure based on the depth of prior experience and educational background.
- Variable compensation through sign-on and year-end bonuses
- Generous benefits, with relocation
- Hybrid schedule: 3 days onsite, 2 days remote
Joining StaffRight Associates
When you partner with StaffRight Associates in your search for your next role, you’re doing more than pursuing a job, you’re aligning yourself with a team of experts committed to placing top-tier talent in truly impactful positions. We take pride in fostering professional growth and connecting forward-thinking individuals with organizations that value innovation and excellence. We look forward to showcasing your expertise in a way that resonates with our clients and opens the door to meaningful opportunities.
