Machine Learning Engineer
Terray TherapeuticsUnited States75 days ago
Full-timeEngineering, Information Technology
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Company Overview: Terray Therapeutics is a venture-backed biotechnology company led by pioneers and long-time leaders in artificial intelligence, synthetic chemistry, automation, and nanotechnology. We’re generating chemical data purpose-built to propel drug discovery into the information age — and we’re doing it on a larger scale and faster than has ever before been possible.
Our closed loop system generates precise chemical datasets at unrivaled scale that work seamlessly with AI to systematically map biochemical interactions between small molecules and causes of disease. Iterative cycles of virtual molecular design and experimentation power AI and machine learning models, which in turn guide the next cycle of design. With a chemistry engine that measures billions of interactions daily and becomes increasingly precise with every cycle, we can answer an unprecedented array of questions — deriving insights that enable us to predictably create drugs for patients in need.
Position Summary: Terray is currently seeking a motivated, creative, and experienced machine learning engineer. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will be responsible for developing and deploying state-of-the-art machine learning models trained on up to billions of small molecule affinity/activity data points in order to accelerate drug discovery efforts internally and for our partners. Researchers in this position have a unique opportunity to test models with very high certainty, and build precise models facilitated by a scale of data unavailable elsewhere.
The Core Responsibilities Of This Position Are
Required Qualifications
Fluent in PyTorch and/or JAX Experience authoring high performance modules for expressive encoders/decoders and/or generators of structured data manifolds Comfortable manipulating data and models in a heterogeneous, multi-cloud, decentralized infrastructure (sql, no-sql, docker, redis, aws, dgx) Experience with distributed model training Familiarity with molecular data manifolds is a plus Willingness to demonstrate mastery of ML in a short (< 6 hr) at-home exercise, or with a preponderance of visible work
Compensation Details: $140,000 - $216,000 (annually) depending on seniority; participation in the Company's option plan; 3% retirement safe harbor contribution; fully-paid medical, dental, vision, life and disability benefits.
Our closed loop system generates precise chemical datasets at unrivaled scale that work seamlessly with AI to systematically map biochemical interactions between small molecules and causes of disease. Iterative cycles of virtual molecular design and experimentation power AI and machine learning models, which in turn guide the next cycle of design. With a chemistry engine that measures billions of interactions daily and becomes increasingly precise with every cycle, we can answer an unprecedented array of questions — deriving insights that enable us to predictably create drugs for patients in need.
Position Summary: Terray is currently seeking a motivated, creative, and experienced machine learning engineer. As an integral member of our Computational and Data Sciences (CDS) team, the candidate will be responsible for developing and deploying state-of-the-art machine learning models trained on up to billions of small molecule affinity/activity data points in order to accelerate drug discovery efforts internally and for our partners. Researchers in this position have a unique opportunity to test models with very high certainty, and build precise models facilitated by a scale of data unavailable elsewhere.
The Core Responsibilities Of This Position Are
- Develop and train transformer-based models on novel, large, multimodal datasets.
- Write modules in a pytorch codebase to encode and decode new chemical and drug data modalities.
- Light curation of datasets.
- Statistical analysis of model performance.
- Deploy models as components to our existing inference and design tools.
- Communicate and Coordinate your experiments with the rest of the Machine Learning Team.
Required Qualifications
Compensation Details: $140,000 - $216,000 (annually) depending on seniority; participation in the Company's option plan; 3% retirement safe harbor contribution; fully-paid medical, dental, vision, life and disability benefits.
Key Skills
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