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Genetics Python Genomics Jobs (NOW HIRING)

Urus

Quantitative Geneticist

Madison, WI · On-site

... genetics through innovative quantitative genetics analysis and technical expertise. This role ... Utilize genomic data and/or machine learning to enhance prediction models. * Collect, organize, and ...

Urus Group LP

Quantitative Geneticist

Madison, WI · On-site

... genetics through innovative quantitative genetics analysis and technical expertise. This role ... Utilize genomic data and/or machine learning to enhance prediction models. * Collect, organize, and ...

AgSource

Quantitative Geneticist

Madison, WI · On-site

... genetics through innovative quantitative genetics analysis and technical expertise. This role ... Utilize genomic data and/or machine learning to enhance prediction models. * Collect, organize, and ...

AgSource

Quantitative Geneticist

Madison, WI

... genetics through innovative quantitative genetics analysis and technical expertise. This role ... Utilize genomic data and/or machine learning to enhance prediction models. * Collect, organize, and ...

Farm Systems

Quantitative Geneticist

Madison, WI · On-site

... genetics through innovative quantitative genetics analysis and technical expertise. This role ... Utilize genomic data and/or machine learning to enhance prediction models. * Collect, organize, and ...

Ohalo

Quantitative Geneticist

South San Francisco, CA · On-site +1

You will be at the nexus of genetics, data science, and engineering, designing the predictive ... Genomic Prediction & GWAS: Design, build, and validate the primary statistical models (e.g., GBLUP ...

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How much do genetics python genomics jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for genetics python genomics in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What are Genetics Python Genomics jobs?

Genetics Python Genomics jobs involve using Python programming to analyze and interpret genetic and genomic data. Professionals in this field work on tasks such as processing DNA sequences, identifying genetic variations, and developing bioinformatics tools to support research in genetics. The role often requires a strong background in biology, genetics, and computer science, particularly in data analysis and software development. These jobs are typically found in research institutions, biotech companies, and healthcare organizations working on precision medicine and genetic research.

How do Genetics Python Genomics professionals typically collaborate with biologists and data scientists in research projects?

Genetics Python Genomics professionals often work closely with biologists to understand experimental goals and interpret genetic data, while also partnering with data scientists to develop and implement robust computational workflows. Collaboration usually involves translating biological questions into analytical tasks, creating and optimizing Python scripts for genomics data processing, and presenting results in a clear, actionable format. Effective communication and interdisciplinary teamwork are key in this role, as projects frequently require integrating knowledge from genetics, programming, and statistics to drive scientific discovery.

What is the difference between Genetics Python Genomics vs Bioinformatics Analyst?

AspectGenetics Python GenomicsBioinformatics Analyst
Required CredentialsBachelor's or Master's in Genetics, Bioinformatics, or related field; proficiency in PythonBachelor's or Master's in Bioinformatics, Computer Science, or related field; programming skills in Python and R
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, healthcare, biotech firms, data analysis teams
Industry UsageGenetics research, genomics data analysis, personalized medicineGenomics, disease research, data interpretation, software development

Genetics Python Genomics focuses on developing Python-based tools for genetic data analysis, often within research or biotech settings. Bioinformatics Analysts also work with genetic data but typically perform broader data interpretation and reporting tasks. Both roles require programming skills and a background in biology or genetics, but Genetics Python Genomics emphasizes coding and tool development, while Bioinformatics Analysts focus on data analysis and insights.

What are the key skills and qualifications needed to thrive as a Genetics Python Genomics specialist, and why are they important?

To excel as a Genetics Python Genomics specialist, you need a solid background in genetics, bioinformatics, and proficiency in Python programming, often supported by a relevant degree such as bioinformatics, computational biology, or genetics. Familiarity with bioinformatics tools (e.g., Biopython, GATK, PLINK), next-generation sequencing platforms, and genomic databases is essential. Strong analytical thinking, attention to detail, and effective communication help in interpreting complex data and collaborating across multidisciplinary teams. These competencies are vital for accurately analyzing genomic data, developing reproducible workflows, and advancing research or clinical applications.
Infographic showing various Genetics Python Genomics job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Machine Learning Engineer - Plant Genomics AI

Machine Learning Engineer - Plant Genomics AI

Boyce Thompson Institute

Ithaca, NY • On-site

$85K - $109K/yr

Full-time

Posted 12 days ago

Job description

Job Type
Full-time
Description
Machine Learning Engineer - Plant Genomics AI
Buckler Laboratory, Boyce Thompson Institute
Position Overview
The Buckler Lab at the Boyce Thompson Institute (BTI) seeks two skilled Machine Learning Engineers to advance our AI research initiatives in plant genetics and genomics. Our lab, based at BTI, Cornell, and USDA-ARS, conducts cutting-edge research working to address three main questions: How can we use genetics to make agriculture more efficient and share those efficiencies globally? How can we reduce the impact of agriculture on the environment? How does genetic variation give rise to phenotypic variation?
Our team develops and maintains sophisticated AI tools and software for genomic analysis and data management, serving our research laboratory, plant breeding programs, and the global genetics research community.
Key Responsibilities
  • Design, train, and evaluate machine learning models for diverse plant genetics applications
  • Deploy production-ready ML models and maintain model performance in operational environments
  • Stay current with state-of-the-art ML methodologies, frameworks, and research developments
  • Support multiple concurrent machine learning projects across various research domains
  • Collaborate with researchers to translate biological questions into ML problem formulations
  • Create compelling data visualizations and communicate results to technical and non-technical stakeholders
  • Contribute to research publications and present findings at scientific conferences

Optimize model performance and computational efficiency for large-scale genomic datasets
What We Offer
Join a world-class research team where your ML expertise will drive breakthrough discoveries in plant genetics and contribute to global food security solutions. Work at the intersection of cutting-edge AI technology and impactful biological research.
Salary Range - $85,000 - $109,000 (within range determined by experience and/or advanced degree)
Remote work option not available, must work onsite in Ithaca, NY
Requirements
Required Qualifications
  • Bachelor's degree in Computer Science, Machine Learning, Bioinformatics, or related field
  • 2-4 years of hands-on experience training and deploying machine learning models
  • Demonstrated proficiency with GPU computing for ML applications
  • Expert-level Python programming skills
  • Extensive experience with modern ML frameworks (PyTorch, HuggingFace, NumPy, scikit-learn)
  • Experience with data preprocessing, feature engineering, and statistical analysis methods for biological data
  • Knowledge of deep learning architectures (CNNs, RNNs, Transformers, etc.)
  • Proficiency in model evaluation and validation techniques (cross-validation, performance metrics, bias detection)
  • Experience with probability and/or applied mathematics, especially with respect to ML/AI modeling
  • Experience handling large datasets and data pipeline development
  • Proven ability to create effective data visualizations and technical reports
  • Strong version control skills using Git
  • Experience with Agile development methodologies and collaborative workflows
  • Proficiency in Linux environments
  • Excellent written and verbal communication skills with ability to explain complex concepts
  • Strong organizational and project management capabilities
  • Demonstrated success working in interdisciplinary team environments
  • Commitment to staying current with rapidly evolving ML landscape

Preferred Qualifications
  • Advanced degree (MS/PhD) in relevant field
  • Experience with additional programming languages (Java, Kotlin, C/C++)
  • Experience with biological/genomic data formats (FASTA, VCF, BAM, etc.)
  • Background in computational biology, bioinformatics, or genomics
  • Experience with cloud computing platforms (AWS, Google Cloud, Azure)
  • Familiarity with MLOps practices and model deployment pipelines
  • Knowledge of statistical genetics or quantitative genetics
  • Experience with distributed computing frameworks
  • Publications in machine learning or computational biology

Salary Description
$85,000 - $109,000

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