Flagshippioneeringinc

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 groundbre

Position Summary:

Quotient is seeking a Director or Senior Director of Antibody Discovery. This role will define and lead Quotient’s antibody discovery strategy; leading the delivery of therapeutic antibody projects in addition to Quotient’s antibody drug discovery platform build through the deployment of cutting-edge technologies. This role will require close involvement in the end-to-end process of translating Somatic Genomics screening outputs (i.e. candidate genes and potential drug targets) into initiation of drug discovery programs. This role will also involve senior project leadership, steering drug discovery matrix teams from early conception through to key inflection points such as development candidate nomination and IND submission.

Responsibilities: 

• Provide balanced expert advice on the feasibility of antibody tractable targets and the conception of high-value drug molecules
• Present antibody discovery strategies to internal R&D committees to justify capital commitment in new programs
• Drive decision making on construct design, format and developability for new antibody programs according to Target Product Profile specifications
• Independently carry out lead sequence and format optimizations utilizing rational, structure-based and in silico/AI/ML design approaches
• Drive rapid optimization of novel antibody and protein therapeutics through iterative design, build, test, and learn cycles
• As a drug discovery project leader, develop efficient and balanced project plans for one or more biologic drug discovery programs and lead a cross-functional team to execute through lead generation, development candidate nomination and IND submission
• Model best matrix leadership behaviours and support an emphasis on enterprise leadership across the company
• Identify, select, and manage external CROs/vendors, consultants, and academic collaborators to deliver a virtual/outsourced state-of-the-art drug antibody discovery platform for the identification of high-quality mAb molecules at pace
• Build and maintain networks of external experts to pressure-test hypotheses and refine strategies
• Serve as a specialist antibody discovery expert within Quotient’s drug discovery team and across the company.
• Contribute to broader corporate strategy, BD evaluations, and exploratory platform initiatives

Qualifications:

Essential

• Proven experience advancing protein therapeutics through drug discovery phases to development.
• Expertise in structure-based protein engineering and design of antibodies including (multispecifics, Fc engineering, fusion proteins etc)
• Skilled in antibody engineering, including use of in silico, structure-based, and AI/ML approaches to sequence/CDR design, use of display technologies, humanization techniques, sequence liability remediation, analytics, and developability (biophysical) assessment and improvement
• Project leadership experience in pharmaceutical industry R&D environment across multiple therapeutic areas, with a deep understanding of lead identification and optimization through preclinical development of antibody therapeutics
• Track record of advocating for acquisition or creation of new technologies for accelerated antibody design, expression, and characterization

Desirable

• Experience in early-stage or start-up biotech environments
• Experience working with genetic and genomics platform-driven drug target discovery
• Broader understanding of protein sciences (expression, developability, and analytical purification and analysis)
• Experience managing the design and validation of cellular assays for the functional characterization of engineered biologics

Values and Behaviors: