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2 дня назад

Staff Scientist, Machine Learning (Genomics)

167 400 - 209 200$
Формат работы
remote (только USA)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Staff Scientist, Machine Learning (Genomics) (Genomics/NGS): Designing and validating machine learning and deep learning models for genetic and clinical sequencing data with an accent on NGS bioinformatics, statistical rigor, and product-focused algorithm development. Focus on tracing results through sequencing pipelines, designing experiments with molecular biology teams, preventing data leakage, and mentoring scientists on complex modeling problems.

Location: US Remote; United States

Salary: USD 167,400–209,200 per year

Company

hirify.global develops cell-free DNA testing and personalized genetic diagnostics for oncology, women’s health, and organ health.

What you will do

  • Lead research on machine learning and deep learning models using NGS data and set technical direction for ambiguous problems.
  • Design, build, benchmark, and validate models and features for Women’s Health and Organ Health products.
  • Run, interpret, debug, and extend sequencing bioinformatics pipelines, tracing issues through processing steps, data, and biology.
  • Partner with molecular biology and assay development scientists on study design, controls, data generation, and experimental troubleshooting.
  • Set standards for validation, performance estimation, leakage prevention, analysis, and technical documentation.
  • Contribute to invention disclosures, patents, publications, and presentations while mentoring data scientists and bioinformaticians.

Requirements

  • M.S. or Ph.D. in computer science, applied mathematics, statistics, bioinformatics, computational biology, engineering, or a related quantitative field; equivalent professional depth is accepted.
  • 6+ years of hands-on machine learning and biological or genomic data analysis experience after the degree, including experience from the point at which work became substantially independent.
  • Track record of leading models or algorithms that reached real use in a product, production pipeline, or relied-upon decision.
  • Depth in NGS data analysis, including sequencing QC, alignment, quantification, normalization, and sequencing artifacts.
  • Ability to independently run, read, debug, interpret, and extend NGS bioinformatics pipelines and their components.
  • Extensive practical experience with machine learning, deep learning, statistics, model validation, and performance estimation on limited or imbalanced data.
  • Advanced Python and experience with open-source machine learning libraries such as scikit-learn, PyTorch, TensorFlow, or XGBoost in a cloud environment.
  • Experience processing large datasets and using a query language such as SQL.
  • Ability to apply mathematical and statistical principles to estimation problems, understand molecular or clinical biomarker assay pipelines, communicate technical results clearly, and deliver complex cross-functional projects.

Nice to have

  • RNA-seq or small RNA/miRNA experience.
  • Probabilistic modeling for NGS and omics data.
  • Diagnostic product development in a regulated or CLIA/CAP setting.
  • Workflow orchestration with Nextflow, WDL, or Snakemake, and containerization with Docker.
  • AWS or GCP experience for large-scale machine learning training and inference.
  • Patents, peer-reviewed publications, or conference presentations.
  • Experience working in a fast-paced, high-impact small-team environment.

Culture & Benefits

  • Remote work is available within the United States.
  • Benefits include medical, dental, vision, life, and disability plans for eligible employees and dependents.
  • Additional benefits include free testing for employees and immediate families, fertility care, pregnancy and baby bonding leave, 401(k), commuter benefits, and an employee referral program.
  • AI tools, including coding agents for implementation, analysis, and review, are part of routine work; ownership of shipped output remains with the employee.
  • hirify.global promotes inclusive collaboration and equal employment opportunity.

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