Senior Machine Learning Scientist

Quotient Therapeutics; Cambridge; On-site; GBP 70,000 - 95,000; Full time

Job summary

Quotient Therapeutics seeks a Machine Learning Scientist to build AI systems that turn complex biology data into actionable insights. You will work at the intersection of ML, genomics, causal biology, and target discovery, delivering models and AI tools to accelerate discovery and decisions.

This is a hands-on role emphasizing clean, reliable code, modern AI tooling, and collaboration with biology, engineering, and discovery teams to shape therapeutic strategies.

Qualifications

• PhD, Master’s degree, or equivalent experience in machine learning, computer science, computational biology, genomics, bioinformatics, statistics, engineering, or a related field.

Responsibilities

• Build ML models for genomic, single-cell, perturbation, and phenotype data.
• Develop agentic AI workflows to help scientists analyze data and test hypotheses.
• Train and fine tune foundation models, language models, and representation learning methods for target discovery.
• Model relationships between genotype, cell state, perturbation response, causal biology, and disease.
• Collaborate closely with computational scientists, experimental biologists, software engineers, and target discovery teams.
• Communicate results clearly, including model assumptions, limitations, and next steps.

Skills

Python programming

Deep Learning

ML system design

AI coding tools / LLM workflows

Education

PhD or MSc in ML/CS/Computational Biology or related

Tools

AI coding tools

LLM-based workflows

Perturb-seq analysis tools

Job description

Position Summary:

We are looking for a Machine Learning Scientist to build AI and machine learning systems that turn complex biological data into actionable scientific insight. You will work at the intersection of ML, genomics, causal biology, and target discovery. The role includes building models, agentic AI workflows, systems that help automate analysis, reasoning, and decision support, and AI assisted tools that help connect genotype, cell state, perturbation, phenotype, and disease mechanism.This is a hands‑on role for someone who enjoys writing clear, reliable code, uses modern AI tools to move faster, and wants their work to shape real biological and therapeutic decisions.

Responsibilities:

• Build ML models for genomic, single-cell, perturbation, and phenotype data.
• Develop agentic AI workflows that help scientists analyze data, test hypotheses, and make better decisions.
• Use AI coding tools to accelerate development while keeping code reliable, readable, tested, and reproducible.
• Train and fine tune foundation models, language models, and representation learning methods for target discovery.
• Model relationships between genotype, cell state, perturbation response, causal biology, and disease.
• Collaborate closely with computational scientists, experimental biologists, software engineers, and target discovery teams.
• Communicate results clearly, including model assumptions, limitations, and next steps.

Qualifications:

You do not need to meet every item to apply. Strong candidates may come from academia, industry, open‑source work, or hands‑on research.

• PhD, Master’s degree, or equivalent experience in machine learning, computer science, computational biology, genomics, bioinformatics, statistics, engineering, or a related field.
• Strong Python coding skills and experience building practical Deep Learning ML systems.
• Experience using AI coding tools, coding assistants, LLM‑based workflows, or agentic development tools.
• Experience training, evaluating, or applying ML models to complex real‑world data.
• Depth in one or more of: biomedical foundation models, agentic AI, Perturb‑seq, single‑cell genomics, genotype–phenotype modeling, causal inference, perturbation modeling, or large‑scale biological datasets.
• Evidence of technical depth through papers, thesis work, open‑source projects, industry projects, or substantial hands‑on applied research.

Values and Behaviors:

• Encourage respectful disagreement and cultivate open‑minded, ego‑free interactions to continuously push each other towards excellence
• Seek out diverse perspectives; practice active listening and genuine curiosity to ensure all contributions are valued, regardless of source
• Recognize the impact of your behavior, language and attitudes, and strive for balanced, meaningful exchanges that enhance mutual growth and understanding in all interactions
• Use a company‑first mindset to guide decision‑making; prioritize team over individual success
• Take calculated risks and challenge convention in the quest for exceptional outcomes

About Quotient:

Quotient Therapeutics is a privately‑held, early stage company developing breakthrough medicines informed by natural somatic genetic diversity present in patients. Through our work in somatic genomics, we are forging a new status quo for biopharma research and development across a broad pipeline of internal and partnered programs.

The company was founded by Flagship Pioneering, an innovative enterprise that conceives, creates, resources, and grows first‑in‑category life sciences companies. Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA), Generate Biomedicines, Sana Biotechnology (SANA), Tessera Therapeutics, Evelo Biosciences (EVLO), Indigo Agriculture, Seres Therapeutics (MCRB), and Syros Pharmaceuticals (SYRS).

Quotient Therapeutics and Flagship Pioneering are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.