Deep Learning Research Engineer - Scientific Discovery at Cyrad Solutions in New York, New York, United States

Job description

• About the job Deep Learning Research Engineer - Scientific Discovery
• Location: New York, NY
• Work Model: Hybrid (in office Tuesday through Thursday, remote Monday and Friday)
• Compensation: $300K to $600K base, plus substantial variable compensation including sign-on and year-end bonuses
• This role sits inside a private scientific research organization that applies machine learning, high-performance computing, and computational science to some of the hardest open problems in molecular science and drug discovery. The environment is closer to a research institute than a product company: long time horizons, deep technical staff, and computing infrastructure built for scientific workloads that most ML teams never touch.
• The position will research and build deep-learning methods for scientific problems where the data, physics, and scale are all nonstandard. The work spans molecular modeling, biological systems, chemical discovery, and simulation, and it requires taking ideas from early experimentation through to working systems that materially change what the research organization can do. Researchers work directly alongside chemists, biologists, physicists, and computational scientists rather than through a handoff.
• This is not conventional applied ML. Candidates who want to work at the boundary of deep learning, scientific computing, and molecular simulation, with the compute to match, will find few comparable roles.

Responsibilities

• Research and develop deep-learning approaches for complex scientific and computational problems
• Apply machine learning to molecular modeling, biological systems, chemical discovery, and large-scale simulation
• Build high-performance ML systems on sophisticated, purpose-built computing infrastructure
• Collaborate directly with researchers across machine learning, chemistry, biology, physics, and computational science
• Carry promising ML ideas from experimentation through to working systems capable of advancing real scientific discovery
• Move quickly into unfamiliar scientific domains and contribute rigorously within them

Requirements

• Exceptional background in machine learning, computer science, mathematics, physics, or another highly quantitative discipline
• Deep experience developing modern deep-learning techniques
• Strong Python programming ability
• Demonstrated ability to conduct rigorous ML research and translate it into working systems
• An exceptional record of academic, research, technical, or professional achievement
• Strong intellectual curiosity and the ability to ramp quickly in new scientific areas
• Ability to work in the New York office three days per week
• Experience in molecular dynamics, structural biology, medicinal chemistry, cheminformatics, quantum chemistry, or a related area (valuable but not required)

Skills

Required

• Deep learning
• Machine learning
• Python
• High-performance computing
• Scientific computing
• Research
• Quantitative discipline

Preferred

• Molecular dynamics
• Structural biology
• Medicinal chemistry
• Cheminformatics
• Quantum chemistry

Benefits

• $300K to $600K base salary, plus substantial variable compensation including sign-on and year-end bonuses. Hybrid schedule with three days per week in the New York City office.