Senior/Principal Scientist, AI/ML

ARTO; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

ARTO is seeking a hands-on Senior Scientist with strong AI/ML expertise to build their computational platform and translate biological data into improved therapeutic designs.

You will develop and fine-tune models, apply ML to genomic data, and collaborate with experimental scientists to integrate results into design cycles. This role requires a PhD/masters and 3+ years of ML experience in biology.

Qualifications

• Master's or PhD in a relevant field.
• ≥3 years AI/ML experience on genomic or complex biological data.
• Hands-on ML model development, not just using tools.
• Proficient in Python; familiarity with R is a plus.
• Experience with RNA-seq, MPRA, ATAC-seq or proteomics data.

Responsibilities

• Develop, train, and fine-tune AI/ML models for genetic medicines.
• Apply ML to genomic sequences to optimize gene expression.
• Analyze MPRA, RNA-seq and functional genomics data.
• Collaborate with experimental scientists to integrate results.
• Develop methods to identify regulatory elements in cancer gene expression.
• Own AI/ML projects from objectives to evaluation.
• Collaborate with external AI research partners.

Skills

AI/ML experience

Python programming

Genomics data analysis

Collaborative team work

Model development

Education

Master's or PhD in Computational Biology

Tools

PyTorch

TensorFlow

R

Job description

ARTO is working with an AI-native company developing next-generation genetic medicines for oncology. The team is combining artificial intelligence, computational biology and experimental science to develop novel approaches to targeted therapeutics. They are looking for a hands-on Senior Scientist with strong AI/ML expertise to help develop their computational platform and play a key role in translating biological data into improved therapeutic designs.

Job Description

• Develop, train and fine-tune AI/ML models, including biological foundation and generative models, to support the design of novel genetic medicines.
• Apply machine learning to genomic sequences and regulatory DNA to predict and optimise gene expression.
• Analyse high-throughput biological datasets, including massively parallel reporter assays (MPRA), RNA-seq and other functional genomics data.
• Work closely with experimental scientists to integrate laboratory results into model development, validation and optimisation.
• Develop computational approaches to identify biological mechanisms and regulatory elements relevant to cancer-selective gene expression.
• Take independent ownership of AI/ML projects, from defining scientific objectives and selecting modelling approaches through to evaluating results.
• Contribute to the development of the company's wider computational capabilities and collaborate with external AI research partners.

Qualifications

• Master's or PhD in Computational Biology, Bioinformatics, Computer Science, Machine Learning or a related discipline.
• At least 3 years of experience applying AI/ML to genomic, bioinformatic or other complex biological datasets.
• Demonstrated hands‑on experience developing, training or fine‑tuning machine learning models, rather than solely applying existing tools.
• Strong programming skills in Python, with experience using modern machine learning frameworks; familiarity with R is advantageous.
• Experience analysing biological datasets such as RNA‑seq, single‑cell RNA‑seq, ATAC‑seq, MPRA or proteomics, with a strong understanding of gene regulation.
• Ability to work independently in a multidisciplinary biotech environment, collaborate with experimental scientists and translate computational results into actionable biological insights.