Machine Learning Scientist / Senior Machine Learning Scientist
Calico Labs is hiring a Machine Learning Scientist / Senior Machine Learning Scientist in South San Francisco, United States. It pays $170k-$240k a year and Level rates it ; you can apply on Calico Labs.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions Python, PyTorch and TensorFlow among its tools and skills.
- Level classes it as a senior role.
- Calico Labs has 20 other open roles on Level.
AI in this role
Design and train deep learning models for biological sequence analysis and gene regulation as a machine learning scientist.
Who We Are:
Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.
Position Description:
Calico is seeking a machine learning scientist to join a research group investigating how genome sequence determines regulatory function and how dysregulation of these programs drives aging. We develop sequence-based deep learning models that predict gene expression, chromatin accessibility, and other functional readouts directly from DNA. We use these models to interpret human genetic variation, map causal regulatory mechanisms, and identify promising intervention points.
This work builds on a sustained research program at the intersection of deep learning and regulatory genomics, including:
- Avsec, Ž. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat Methods 18, 1196–1203 (2021).
- Yuan, H. & Kelley, D. R. scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks. Nat Methods 19, 1088–1096 (2022).
- Linder, J., Srivastava, D., Yuan, H., Agarwal, V. & Kelley, D. R. Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation. Nature Genetics (2025).
Additional research can be found here.
Position Responsibilities:
- Design and train deep learning models for biological sequence analysis, with emphasis on gene regulation, single-cell genomics, and variant interpretation
- Partner with experimental scientists to connect model predictions to biological mechanisms — designing validation experiments, analyzing large-scale genomics data, and translating computational findings into actionable biological insights
- Communicate research through publications, open-source software, and public-facing tools
Position Requirements:
PhD in computational biology, bioinformatics, computer science, or a related field, and 0-5 years (for Scientist level) or 5+ years (for Senior Scientist level) of additional training in an industry or academic setting, with a strong publication record
- Deep expertise in machine learning with solid grounding in algorithms, data structures, and statistics
- Substantive knowledge of molecular biology and genetics; familiarity with genomic data types and public data resources
- Hands-on experience analyzing genomics sequencing data, ideally including single-cell assays
- Fluency with modern AI-assisted development and research tools (e.g., LLM-based coding assistants, literature synthesis), with a habit of proactively integrating new tools to accelerate scientific workflows
- A collaborative disposition, strong follow-through, and comfort working at the interface of computation and experiment
- Must be willing to work onsite at least four days per week
The estimated base salary range for this role is $170,000 - $240,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses
How we rate this
Machine Learning Scientist / Senior Machine Learning Scientist at Calico Labs rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where computational biology was part of your work. What did you do?
- Tell me about a project where genomics was part of your work. What did you do?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where bioinformatics was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Machine learning, Computational Biology, Genomics, Deep learning, and Bioinformatics. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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