Machine Learning Engineer

R&D Partners; South San Francisco (CA); In loco; USD 135.000 - 169.000; Tempo pieno

Vantaggi offerti da questo lavoro

Medical insurance – PPO, HMO & HSA

401k plan

Employee Assistance Program

Long-term disability

Weekly payroll

Online timecard approval

Descrizione del lavoro

R&D Partners seeks a talented Machine Learning Engineer to advance molecular design using ML-based optimization and probabilistic modeling. You will build pipelines for molecular property prediction and active learning in drug discovery, collaborating with ML scientists, chemists, and biologists in a fast-paced environment.

The role focuses on deploying production-ready ML workflows with Bayesian optimization and generative modeling for drug design, in a 12-month contract based in South San

Competenze

• PhD in Computer Science, Chemistry, Chemical Engineering, Computational Biology or Physics; or MS with 3+ years industry experience.
• Experience with ML libraries in production-grade workflows such as PyTorch + Lightning + Weights & Biases.
• Demonstrated track record: at least one high-impact first-author publication or equivalent.
• Strong written, visual, and oral communication and collaboration skills.
• Experience with physical modeling methods (molecular dynamics) and cheminformatics toolkits (e.g. rdkit).
• Focus on one or more areas: molecular property prediction, computational chemistry, de novo drug design, etc.
• Public portfolio of computational projects (e.g., GitHub).
• Salary range appears in ad: $134,908-$168,646.

Mansioni

• Develop ML and Bayesian optimization workflows to analyze and design small and large molecules.
• Collaborate with ML scientists, engineers, computational chemists, and computational biologists.
• Engage with small molecule and protein therapeutic development efforts.
• Generate new project ideas and contribute to ongoing projects.

Conoscenze

ML workflows

Communication

Collaboration

Portfolio of computational projects

Formazione

PhD in a quantitative field or MS + 3+ years industry

Experience with ML libraries in production (PyTorch + Lightning + Weights & Biases)

Strumenti

PyTorch

Lightning

Weights & Biases

rdkit

Molecular dynamics tools

Descrizione del lavoro

Get AI-powered advice on this job and more exclusive features.

This range is provided by R&D Partners. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$134,908.00/yr - $168,646.00/yr

We are looking for a talented Machine Learning Engineer to develop structural and machine learning based methods for molecular design. The candidate will manage projects deploying new techniques for machine learning based molecular optimization for the analysis and design of small and large molecule drugs within target-driven design campaigns. Special focus will be given to engineering pipelines for probabilistic molecular property prediction and Bayesian acquisition for active learning based drug discovery. Additional activities may extend to include engineering pipelines for molecular generative modeling.

This is a 12-month contract based in South San Francisco, California.

Responsibilities

• Your peers will be machine learning scientists, engineers, computational chemists, and computational biologists.
• You will develop machine learning and Bayesian optimization workflows to analyze existing, and design new, small and large molecules.
• You will be expected to form close working relationships with small molecule and protein therapeutic development efforts.
• You will be expected to work on existing projects and generate new project ideas.

Qualifications

• PhD degree in a quantitative field (Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics) or MS degree and 3+ years of industry experience.
• Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases).
• Record of achievement, including at least one high-impact first author publication or equivalent.
• Excellent written, visual, and oral communication and collaboration skills.
• Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g. rdkit).
• Previous focus on one or more of these areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, statistical methods.
• Public portfolio of computational projects (available on e.g. GitHub).
• $134,908-$168,646

Why Choose R&D Partners?

• Medical insurance – PPO, HMO & HSA
• 401k plan
• Employee Assistance Program
• Long-term disability
• Weekly payroll
• Online timecard approval

R&D Partners is a global functional service provider and strategic staffing resource specializing in scientific, clinical research & engineering. We provide job opportunities within major pharmaceutical, biopharmaceutical, biotechnology, and medical device companies.

R&D Partners is an equal-opportunity employer.

Seniority level

• Seniority levelAssociate

Employment type

• Employment typeContract

Job function

• Job functionResearch
• IndustriesStaffing and Recruiting and Biotechnology Research

Referrals increase your chances of interviewing at R&D Partners by 2x

Inferred from the description for this job

Medical insurance

Vision insurance

401(k)