Elegen is blazing a path towards a biology-based economy with a highly innovative approach to DNA synthesis that delivers an industry leading length of 7kb in 7 business days with a 99.999% per base accuracy. Our multidisciplinary team of best-in-class biologists, chemists, hardware, and software engineers apply cutting-edge technologies and methods to solve critical bottlenecks in synthetic biology workflows to help our customers in pharma, biotech, agbio, and biomanufacturing streamline their work and realize the full potential of programmable biology.
We are looking for a machine learning engineer to create quantitative and incisive analyses of DNA sequence attributes and NGS data. The role will include opportunities to develop analyses ranging from early-stage research experiments to production pipelines and databases. You will work closely with molecular biologists as well as the scientific computing team.
This is an opportunity to join a rapidly growing company at an early stage and to have an impact on the development of its products, markets, processes, people, and culture.
Essential Responsibilities:
- Develop algorithms and machine learning models to advance Elegen’s novel synthetic DNA production platform.
- Visualize data and evaluate predictions to inform collaborators about the impact of models on current and future products.
- Identify model architectures, feature sets, hyperparameters, and metrics for optimal model performance.
- Apply machine learning and feature engineering to identify potential improvements to Elegen’s processes and products.
- Manage datasets for model training and feature investigation.
- Collaborate with software teams to integrate machine learning models into commercial workflows.
Essential Qualifications and Experience:
- B.S. with 3+ years of experience or M.S. in machine learning or data science.
- Ability to collaborate and communicate effectively with bench science and software teams.
- Proficiency in Python.
- Knowledge of database architecture and querying (SQL).
- Familiar with software development best practices, including version control using GitHub, testing, and tracking (Jira).
Preferred Qualifications and Experience:
- Experience with ML model integration in production environments in AWS.
- Proficiency in Rust or C#/C++ (Rust is preferred).
- Experience with development of AI/ML methods for biological applications.
- Familiarity with molecular biology reactions and methods.
- Familiarity with gene synthesis methods.
Salary and Benefits:
The annual base salary compensation for this role, if based in California is: $140,000 - $180,000. Compensation may be different in other locations. Final compensation also includes bonus, equity and benefits. Specific offer packages are determined by multiple factors, including candidate skill, experience, expertise, and location.
✓ Healthcare ✓ Dental ✓ Vision ✓ Learning Allowance
✓ 401K ✓ Flexible PTO ✓ Short Term Disability ✓ Fitness Allowance
Founded and led by Dr. Matthew Hill and located in San Carlos, CA, Elegen is well-capitalized by top life science investors, including Andreessen Horowitz, 8VC, and KdT. The company is advised and staffed by leading biotechnology scientists and entrepreneurs, including Dr. Marc Unger, inventor of the Nanoflex™ valve, and former CSO of Fluidigm. Dr. Hill has a PhD from Stanford and a proven track record of advancing innovative technologies from invention to commercial success. Over eight years in his previous role as VP of R&D at a leading molecular diagnostics company, he co-invented and launched five precision molecular diagnostic products, including a best-in-class noninvasive prenatal test used by millions. These products earn more than $350 million per year in revenue and enabled an IPO.
Elegen is an Equal Opportunity Employer.
Elegen provides equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic characteristics, or any other category protected by law. All applicants have rights under the following Federal Employment Laws:
