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How much do single cell omics jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for single cell omics in the United States is $21.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.83 and $27.16 per hour, depending on experience, location, and employer.

What are Single Cell Omics?

Single Cell Omics refers to a group of advanced techniques used to analyze the molecular characteristics of individual cells, rather than averaging data across entire cell populations. These methods include single-cell genomics, transcriptomics, proteomics, and metabolomics, allowing researchers to study genetic, RNA, protein, and metabolic profiles at the single-cell level. This approach helps uncover cellular heterogeneity, understand complex biological processes, and can lead to discoveries in areas like cancer research, developmental biology, and personalized medicine.

What are the key skills and qualifications needed to thrive as a Single Cell Omics Scientist, and why are they important?

To thrive as a Single Cell Omics Scientist, a strong background in molecular biology, genomics, and bioinformatics is essential, typically supported by a PhD or advanced degree in a relevant field. Expertise in single-cell sequencing technologies, computational analysis tools like Seurat or Scanpy, and familiarity with next-generation sequencing platforms are commonly required. Strong analytical thinking, attention to detail, and effective communication skills help professionals collaborate across multidisciplinary teams and present complex data. These skills and qualities are crucial for generating high-quality data, driving scientific discoveries, and translating findings into impactful biological insights.

What is the difference between Single Cell Omics vs Bioinformatics Analyst?

AspectSingle Cell OmicsBioinformatics Analyst
Required CredentialsMaster's or PhD in Biology, Genomics, or related fieldsBachelor's or Master's in Bioinformatics, Computer Science, or related fields
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, biotech firms, healthcare organizations
Industry UsageGenomics, personalized medicine, developmental biologyData analysis, software development, research support

Single Cell Omics specialists focus on analyzing individual cell data to understand cellular heterogeneity, often requiring advanced laboratory skills and genomics expertise. Bioinformatics Analysts interpret large datasets, including genomic data, using computational tools. While both roles involve data analysis, Single Cell Omics is more lab-intensive and specialized in single-cell techniques, whereas Bioinformatics Analysts work across various data types and applications.

What are common challenges faced when working in Single Cell Omics research roles?

Professionals in Single Cell Omics often encounter challenges related to handling and interpreting large, complex datasets generated from individual cells. Maintaining sample quality and minimizing technical variability are crucial for reliable results. Additionally, integrating data across different omics platforms (such as genomics, transcriptomics, and proteomics) requires strong collaboration with bioinformaticians and other specialists. Staying updated with rapidly evolving technologies and analytical methods is also key to success in this field.
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Single Cell Omics jobs near you
Infographic showing various Single Cell Omics job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $45,021 per year, or $21.6 per hour.

Machine Learning Engineer - Biological Foundation Models

Metric Bio

Boston, MA

Full-time

Posted 25 days ago

Job description

Machine Learning Engineer – Biological Foundation Models

Metric Bio has partnered with a venture-backed biotech at the intersection of AI and cell biology. This team is building foundation models on trillion-token scale biological datasets to reimagine how we create cell therapies.

This is a role for someone who doesn’t just apply existing methods but creates new ones; first-author researchers, system builders, and innovators who want their work to drive real therapeutic impact.

Responsibilities:

  • Design and optimize foundation models for single-cell and multi-omics data, leveraging transformer and generative architectures.
  • Build scalable distributed pipelines (multi-GPU training, trillion-token inference) to push biology into true foundation-scale.
  • Collaborate closely with computational biologists and wet-lab teams, ensuring models produce interpretable, biologically meaningful outputs.
  • Prototype and deploy novel architectures tailored to biological data, with the freedom to shape strategy and direction.

Requirements:

  • First-author publications in top-tier ML/biology journals.
  • 6+ years of experience in ML, deep learning, or foundation models (academic or industry).
  • Proven expertise with transformers, diffusion, or generative models.
  • Strong Python + PyTorch/TensorFlow engineering skills; ability to move from research prototype → production.
  • Background in single-cell or omics data is ideal, but ML-first innovators who can quickly learn the biology are very welcome.
  • Track record of innovation: new methods, impactful papers, or deployed ML systems.

What We Offer:

  • Technical leadership opportunity at a mission-driven company that has recently secured over $50M in funding.
  • Work alongside top talent at the cutting edge of AI x biology.
  • Chance to impact millions of lives by redefining how cell therapies are developed.
  • Competitive compensation and benefits, with an emphasis on urgency, collaboration, and innovation.
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