Senior Machine Learning Scientist

About the role

We are seeking a highly skilled Senior Machine Learning Scientist to join our team at Flagship Pioneering, Inc. in Cambridge, UK. This role involves developing advanced AI and machine learning solutions that can interpret and transform complex biological data into actionable insights. The position requires working at the forefront of integrating machine learning techniques with genomics, causal biology, and target discovery efforts. The successful candidate will be instrumental in creating models, designing innovative AI workflows, and developing systems that enhance data analysis, reasoning, and decision-making processes across various biological datasets. This role offers an exciting opportunity to contribute to cutting-edge research and innovation in the biotech space, collaborating closely with multidisciplinary teams to push the boundaries of biological understanding through AI.

Key facts

What you'll do

• Develop and implement machine learning models tailored for genomic, single-cell, perturbation, and phenotype datasets to extract meaningful biological insights.
• Design and optimize AI workflows that support scientists in analyzing complex biological data, testing hypotheses, and making informed decisions.
• Utilize AI coding tools and coding assistants to accelerate development cycles, ensuring that code remains reliable, readable, and reproducible for long-term use and collaboration.
• Train, evaluate, and fine-tune foundational models, language models, and representation learning techniques to facilitate target discovery and biological understanding.
• Analyze the relationships among genotype, cell state, perturbation responses, causal biology, and disease mechanisms to uncover novel insights and therapeutic targets.
• Collaborate effectively with a multidisciplinary team comprising computational scientists, experimental biologists, software engineers, and target discovery specialists to ensure seamless integration of AI solutions into broader research workflows.
• Communicate complex findings clearly to both technical and non-technical stakeholders, including detailed explanations of model assumptions, limitations, and potential next steps.
• Contribute to the development of innovative AI methodologies and tools that can be applied to large-scale biological datasets, advancing the company's research objectives.
• Stay current with emerging trends and advancements in machine learning, genomics, and related fields to continuously improve modeling approaches and workflows.
• Support the documentation of models, workflows, and research findings to facilitate reproducibility and knowledge sharing within the organization.
• Participate in regular team meetings, research discussions, and project planning sessions to align AI development efforts with overall scientific goals.

Requirements

• A PhD, Master's degree, or equivalent experience in machine learning, computer science, computational biology, genomics, bioinformatics, statistics, engineering, or a related discipline.
• Proven proficiency in Python programming, with extensive experience in developing practical deep learning and machine learning systems.
• Familiarity with AI coding tools, coding assistants, large language models (LLMs), and agentic development tools to streamline AI workflows.
• Demonstrated experience in training, evaluating, and applying machine learning models to complex, real-world biological datasets, such as genomics, single-cell data, or perturbation screens.
• Expertise in one or more of the following areas: biomedical foundation models, agentic AI, Perturb-seq, single-cell genomics, genotype-phenotype modeling, causal inference, perturbation modeling, or large-scale biological data analysis.
• Strong publication record, thesis work, open-source contributions, or industry projects that showcase technical expertise and innovative problem-solving skills.
• Ability to work independently and collaboratively within a multidisciplinary team environment.
• Excellent communication skills, with the ability to clearly articulate complex technical concepts and research findings to diverse audiences.
• A strong interest in applying AI to biological research and a passion for advancing scientific discovery through computational methods.

Nice to have

• Experience working in collaborative research environments or interdisciplinary projects that involve both computational and experimental teams.
• Knowledge of additional programming languages or tools relevant to bioinformatics and machine learning.
• Familiarity with cloud computing platforms and data management strategies for large-scale biological datasets.
• Prior experience with regulatory considerations or ITAR compliance in biotech research settings.

Skills & tools

• Proficiency in Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
• Knowledge of genomics, bioinformatics tools, and methodologies used in biological data analysis.
• Experience with data visualization and statistical analysis tools to interpret model outputs effectively.
• Strong problem-solving skills and the ability to adapt to rapidly evolving research challenges.
• Ability to develop scalable, robust, and reproducible AI workflows that can be integrated into larger research pipelines.
• Familiarity with version control systems such as Git to manage code collaboratively.

Practical notes

• Candidates must be eligible to work in the UK to be considered for this position.
• Flagship Pioneering is committed to fostering a diverse and inclusive workplace environment. We actively encourage applications from individuals of all backgrounds, regardless of race, ethnicity, gender, sexual orientation, age, disability, or veteran status.
• We value innovation, curiosity, and a collaborative spirit, and seek candidates who are eager to contribute to groundbreaking biological research through AI.
• Please note that we do not accept unsolicited resumes from recruitment or staffing agencies. All applications should be submitted directly through our official channels.
• The role involves on-site work at our Cambridge, UK office; remote work options are not specified.
• The position may involve working with sensitive biological data, and adherence to data privacy and security protocols is essential.
• Candidates should be prepared to discuss their previous research, technical skills, and how they can contribute to our mission during the interview process.