Machine Learning Engineer, Functional Assay

San Francisco, California, United States

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Posted 1 month ago

Invitae is a rapidly growing, science- and technology-driven company. Our mission is to empower doctors,  patients and individuals to apply genetic and genomic guidance at all stages in life. The Scientific Modeling team plays a critical role in building biological and clinical learning capabilities that enable robust, quantitative, mechanistic, and scalable systems to deliver such guidance.

Invitae’s Scientific Modeling team is hiring talented and motivated Machine Learning Engineers/Scientists with deep expertise to drive cutting-edge research and improvements in statistical modeling and inference of biological problems (including cellular biology, functional genomics,, therapeutics, and more). As a core member of the team, the primary responsibility of Machine Learning Engineers/Scientists is to develop, validate, and deploy models and core analyses in support of integrated computational and cellular systems that can provide critical insights in clinical genetic and genomic tests for >500,000 patients a year. Our team is highly cross-functional and multi-disciplinary. You will work along-side genomic scientists, biophysicists, cellular engineers, data scientists, ML engineers, software engineers, genetic counselors, and medical geneticists to bring improved healthcare to patients.

Our team is committed to advancing the science and technology that underpins application of genomic and molecular data. This commitment requires us to integrate and foster the knowledge and growth of diverse domains in biological, computational, and clinical sciences. Your ability to develop and apply advanced machine learning solutions and quantitative analyses in conjunction with complex assays generating diverse arrays of biological data will help define state-of-the-art genetic testing.

What you’ll do:

  • Design, develop, and validate new machine learning models that can uncover and describe the relationship between genetic and genomic variation, cellular phenotypes, and clinical conditions and symptoms.
  • Design, develop, and validate new methods for characterizing variation in large cellular populations assayed in high-throughput, multi-dimensional assays.
  • Develop, implement, and validate the application and use of modern machine learning and artificial intelligence techniques –applying robust statistical and quantitative methods for the design of experiments– to allow rigorous model evaluation, uncertainty quantification, prediction, and data generation.
  • Integrate advances in diverse fields of machine learning and computer science into modern analytics infrastructure and workflows.
  • Work in a highly collaborative and cross-disciplinary team to advance technology platforms aimed at delivering robust, quantitative, mechanistic, and scalable clinical genetic and genomic testing.

What you bring: 

  • Advanced degrees (e.g. Ph.D. or M.Sc.) in a relevant, quantitative field such as Computer Science (AI or ML emphasis), Statistics, Applied Mathematics, Engineering, Biophysics/Physics, Computational Biology, or a related field.
  • Expertise demonstrated by research publications or industrial experience in modern, applied machine learning, data mining, pattern recognition, or artificial intelligence. Direct experience with and application to the analysis of complex biological datasets and phenomena is ideal.
  • Strong knowledge of mathematical fundamentals: statistics, probability theory, linear algebra.
  • Practical and theoretical understanding of fundamental models and algorithms in supervised and unsupervised learning: generalized linear models, kernel machines, decision trees, neural networks; boosting and model aggregation; clustering and mixture modeling; Bayesian inference and model selection, EM, variational inference, Gaussian processes, causal inference, Monte Carlo methods; dimensionality reduction and manifold learning
  • Ability to work independently, design and conduct research, and to evaluate, interpret and present complex scientific data.
  • Ability to work effectively in a highly cross-functional environment where collaboration across disciplines is a key component for team success.
  • Excellent verbal and written communication and presentation skills.
  • Fluency in programming in Python.

At Invitae, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.

Job tags: AI Data Mining Engineering Healthcare Industrial Machine Learning ML Python Research
Job region(s): North America
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