18 Amgen jobs in South San Francisco

Septerna is a biotechnology company based in South San Francisco, CA on a mission to develop life-changing medicines for patients with the vision to become the industry-leading G protein-coupled receptor (GPCR)-focused drug discovery company. The company's Native Complex Platform™ recapitulates GPCRs with their native structure, function, and dynamics outside of the cellular context. This approach enables novel access to modern structural and screening technologies used in industrial-scale drug discovery for the entire class of GPCRs. Septerna has an emerging pipeline of GPCR-targeted small molecule programs with potential for growth to target many GPCRs that have been undruggable and unexploited to date.

We are excited to expand our multidisciplinary team of individuals focused on creating revolutionary medicines to address the unmet needs of patients. At Septerna we strive to embrace diversity of thought, expertise, and background through collaboration. To join our ambitious team, be prepared to bring your real self to work every day; grow and learn from a talented team of drug hunters, scientists, and business professionals; and contribute your passion, creativity, and energy to accomplish our mission. We share a fearless pursuit of ground-breaking innovations and cultivate an environment where our employees succeed by learning from each other and working as a team.

We are committed to the development of meaningful therapeutics for patients with indications of high unmet need. This is a tremendous opportunity to work with talented individuals on the frontlines of therapeutic discovery and development. You will directly help move therapies through preclinical research, positioning them for success in the clinic. The successful candidate will add their passion, unique talents, and expertise to a dynamic team motivated to discover new disease-modifying therapeutics for patients in a fast-paced environment.

For more information see:

THE ROLE

Septerna is seeking a Data Scientist to join our Data Science and ML team. In this role, you will be instrumental in transforming complex experimental data into actionable scientific insights. You will draw on your data analysis and visualization skills to answer critical scientific questions that will help us optimize experimental protocols, increase our hit rates, and deepen our understanding of the results from our DEL screens. This is an opportunity to join a dynamic team as a data scientist with a passion for science and a desire to make a tangible impact on research and development.

QUALIFICATIONS

• Master's degree (with a minimum of 6 years of experience) or Ph.D. in a quantitative scientific field (e.g., Chemistry, Biology, Bioinformatics, Data Science, Computer Science) with 2+ years of relevant experience.
• Proficiency in Python for data analysis, including extensive experience with libraries such as Pandas, NumPy, and Scikit-learn.
• Demonstrated ability to write clean, modular, and well-documented code, ensuring reusability and maintainability within a shared codebase.
• Strong understanding of data science and statistical concepts and their practical application in experimental contexts.
• Demonstrated ability to create clear and insightful data visualizations.
• Experience with querying and working with databases.
• Familiarity with scientific data, particularly in chemistry and/or biology, and an eagerness to learn more about drug discovery.
• Basic understanding of machine learning principles.
• Excellent problem-solving skills, attention to detail, and a collaborative mindset.
• Strong verbal and written communication skills for interacting with diverse scientific teams.

• Experience with dashboarding tools (e.g., Streamlit, Dash, ReTool).
• Experience with cloud computing platforms (e.g., AWS, Google Cloud) for data storage, processing, and analysis.
• Prior experience in a pharmaceutical, biotechnology, or life sciences research environment.

• Analyze diverse experimental datasets (e.g., from high-throughput/DEL screening or assay results) or ML-derived datasets to identify trends, patterns, and anomalies.
• Apply statistical methods and core data science techniques (e.g., clustering, correlation analysis, statistical metrics) to derive meaningful conclusions from scientific data.
• Develop clear and compelling data visualizations, reports, and/or interactive dashboards to effectively communicate findings to chemists, biologists, and fellow data scientists.
• Collaborate closely with experimental scientists to understand their data needs, optimize experimental designs, and improve data collection strategies.
• Query, extract, and integrate data from various data sources, including SQL/serverless databases.
• Contribute to the development, documentation and maintenance of robust data analysis pipelines (GitHub).
• Maintain a basic understanding of machine learning concepts and evaluate opportunities for their application.
• Stay updated on best practices in data analysis, visualization, and scientific data management.

• Conceptualize, design, and execute complex experiments to identify and validate novel drug targets.
• Develop and optimize high-throughput screening assays for hit identification and lead optimization.
• Lead cross-functional teams of scientists in early-stage drug discovery programs.
• Analyze and interpret large datasets, employing statistical and bioinformatics tools.
• Drive the progression of candidate molecules through preclinical development milestones.
• Collaborate closely with medicinal chemists, pharmacologists, and toxicologists.
• Stay abreast of the latest scientific literature and technological advancements in drug discovery.
• Prepare research proposals, grant applications, and contribute to patent filings.
• Present research findings at international scientific conferences and in peer-reviewed publications.
• Mentor and guide junior scientists and research associates.
• Contribute to the strategic direction of the company's R&D pipeline.

• Ph.D. in Molecular Biology, Biochemistry, Pharmacology, or a related life science discipline.
• Minimum of 8 years of relevant post-doctoral and industry experience in drug discovery.
• Demonstrated expertise in target validation, assay development, and small molecule drug discovery.
• Proven experience leading drug discovery programs from target identification to preclinical candidate selection.
• Strong track record of scientific publications in reputable journals and presentations at international meetings.
• Proficiency in modern molecular biology techniques, cell-based assays, and biochemical methods.
• Excellent analytical, problem-solving, and critical thinking skills.
• Exceptional leadership, communication, and interpersonal skills.
• Experience with biologics discovery is a plus.
• Ability to thrive in a fast-paced, collaborative, and intellectually stimulating environment.

Project Manager - (Early Drug Discovery) This range is provided by Enigma Search. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $130,000.00/yr - $50,000.00/yr Summary We’re seeking a highly organized and scientifically knowledgeable Project Manager to support early discovery programs from target identification through antibody development and IND nomination. This full-time role is ideal for a junior-level professional (2–3 years of experience) who excels in a fast-paced environment, managing timelines, cross-functional resources, and scientific operations. Key Responsibilities: Drive project planning from target selection to antibody generation, assay development, and IND nomination Develop and maintain detailed project timelines using project management software Monitor and reallocate resources (approximately 20 team members across multiple programs) based on changing priorities Collaborate with scientists, CMC, and finance teams to track progress, deliverables, and budgets Translate complex scientific workflows into operational milestones Coordinate cross-functional activities with department leads Qualifications: 2–3 years of project management experience in biotech or life sciences Knowledge of biologics and antibody discovery processes is required Experience with early-stage discovery and CMC workflows Strong communication skills and a proactive, confident personality Proficient in project tracking tools (e.g., Smartsheet, MS Project, or similar) Detail-oriented with a passion for scientific innovation Ability to manage competing priorities and balance scientific and operational goals Comfort working across diverse functions, from bench scientists to finance Seniority level Mid-Senior level Employment type Full-time Job function Project Management Referrals increase your chances of interviewing at Enigma Search by 2x. Set job alerts for “Project Manager” roles. Additional roles: San Mateo, CA: $148,200.0 - 222,400.00 (3 weeks ago) San Francisco, CA: 78,800.00- 120,900.00 (2 weeks ago) San Francisco Bay Area: 180,000.00- 220,000.00 (3 weeks ago) Foster City, CA: 105,000.00- 150,000.00 (1 week ago) #J-18808-Ljbffr

A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche.

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

The Opportunity

At Prescient Design, part of Genentech, we are at the forefront of transforming drug discovery through Artificial Intelligence and Machine Learning. We are building the Lab-in-the-Loop, Genentech's cutting-edge AI platform for therapeutic molecular design. ( ). This platform is central to accelerating the discovery of new medicines by integrating massive quantities of experimental data to train predictive AI models. We seek an exceptional Principal Software Engineer to take a leading technical role in shaping the design, development, and future direction of this critical platform, enabling AI-driven drug design across Roche. We are seeking a technical leader with deep full-stack expertise, particularly skilled in building intuitive front-end experiences and scalable backend systems. The ideal candidate possesses strong product intuition, a keen eye for user experience, and proven experience in shaping technical roadmaps and designing robust service architectures for complex platforms. You thrive on technical ownership and guiding the evolution of a product from concept to production, influencing its capabilities and impact.

You will collaborate closely with Prescient's AI scientists and engineers, Genentech Computational Sciences (gCS) colleagues, including machine learning specialists, Genentech Research & Early Development (gRED) Drug Discovery teams like Antibody Engineering, and other teams across the Roche group. Your role will be key in identifying, strategizing, and productionalizing high-impact AI applications across the drug discovery pipeline. Prescient Design offers a dynamic environment for cutting-edge, multidisciplinary research in AI and drug discovery, providing access to rich data sources, close links to top academic institutions, and internal Genentech and Roche partners.

In this role, you will:

• Contribute to the strategic roadmap for the Prescient "Lab-in-the-Loop" platform, guiding product features and technical architecture to maximize AI impact in drug discovery.

• Take a leading role in the full-stack design and development of scalable, reliable software systems, including crafting responsive and intuitive front-end applications that form the core of our AI/ML platform.

• Collaborate closely with Machine Learning Scientists, AI Engineers, and experimental specialists, translating complex scientific workflows into intuitive user interfaces, dashboards, and analytics tools with a strong focus on user experience.

• Explore and implement integrations with novel AI agents and models to enhance platform capabilities and automate complex tasks.

• Mentor and provide technical guidance to other software engineers on the team, fostering best practices and high-quality engineering.

Who you are

• 10 + years of software engineering work experience, delivering complex, full-stack applications.

• Proven expertise in front-end development using modern frameworks (e.g., React, Angular) and building intuitive, user-centered interfaces.

• Intense curiosity about the biology of disease and eagerness to contribute to scientific and computational efforts.

• Proficiency with Python and SQL

Preferred

• Familiarity with ML concepts or frameworks (e.g., PyTorch).

• Domain experience in drug discovery, computational biology, bioinformatics and cheminformatics
  

Relocation benefits are available for this job posting

The expected salary range for this position, based on the primary location of New York is $155,500 - 288,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.

Benefits

#ComputationCoE

#tech4lifeComputationalScience

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.

If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

• Design and develop multimodal foundation models for gene regulation and drug response
• Integrate chemical structure, protein sequences, and single-cell transcriptomics into unified models
• Adopt and implement latest advances in deep learning (e.g., self-supervised learning, FSDP, dMoE)
• Work in cross-functional teams with biologists, engineers, and data scientists
• Drive hypothesis generation using ML and contribute to novel biological insights

• PhD or equivalent practical experience in a technical/ML-focused field
• Proven experience with deep learning (transformers, GNNs, SSMs, diffusion models, etc.)
• Strong skills in PyTorch, JAX, or TensorFlow, and scientific libraries like NumPy, Pandas
• Motivation to apply ML to real-world biological or chemical datasets
• Bias toward rapid prototyping and practical outcomes

• Prior work in computational biology or drug discovery
• Experience with contrastive/multimodal/self-supervised learning
• Familiarity with large-scale distributed training and GPU optimizations

• Python, PyTorch/JAX/TensorFlow
• Large-scale ML toolkits (e.g., flash attention, FSDP)
• Transcriptomics, protein sequence data, chemical structure modeling

• Unlimited PTO
• Monthly lunch allowance + remote office setup stipend
• Premium medical, dental, and vision coverage for employees and dependents
• Hybrid flexibility from South San Francisco or Toronto

ProGen Search is seeking an Executive Director of Drug Discovery for a biotechnology company specializing in oncology therapeutics. This role leads discovery efforts, driving programs from target identification through preclinical development.

• Oversee oncology drug discovery programs, ensuring alignment with corporate strategy.
• Lead cross-functional teams in target validation, lead optimization, and preclinical development.
• Collaborate with external partners and CROs to advance discovery programs.
• Stay abreast of emerging technologies and integrate them into discovery efforts.
• Present program updates to executive leadership and stakeholders.

• PhD in life sciences or related field.
• 15+ years of experience in oncology drug discovery, with a proven track record in advancing programs to IND-enabling studies.
• Strong leadership and team management skills.
• Expertise in oncology drug development.
• Excellent communication and presentation skills.

If you want to apply, fill in the form below or alternatively, send an email directly to

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The Position A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide. The Opportunity The Large Molecule Drug Discovery group within AI for Drug Discovery seeks exceptional researchers who have a demonstrated research background in protein design and protein structure prediction/analysis, machine learning, project execution, a passion for research collaboration and technical problem-solving, and a proven ability to implement ideas and develop and/or apply methods for large molecule drug discovery. The group provides a dynamic and challenging environment for cutting-edge, multidisciplinary research including access to heterogeneous data sources, close links to top academic institutions around the world, as well as internal Genentech Research and Early Development (gRED) partners and research units. Our mission is to develop and apply physics and machine learning based methods to design novel macromolecules with therapeutic potential. Researchers in this role will develop, manage, and apply computational approaches for large molecule property prediction and de novo generative design, leverage multi-modal data sources including protein structure, protein property, and next-generation sequencing (NGS) data towards portfolio impact. You will play a pivotal role in supporting, applying, and advancing the next generation of l arge molecule generative machine learning models for drug discovery. We seek an individual who is not only passionate about teamwork and technical problem-solving but also has a proven track record of delivering innovative solutions in machine learning and protein engineering. Your responsibilities will include data preparation and cleaning, deploying both internal and external discriminative and generative models, and closely collaborating and communicating with colleagues in Genentech's antibody engineering department to engineer new antibody molecules using the lab-in-the-loop framework. In this role, you will: Develop and/or apply novel Computational Biology/Machine Learning methods to answer challenging research questions in LMDD. Work with biological data from heterogeneous sources. Collaborate closely with cross-functional teams across gRED to solve complex problems including developing models to predict antigen-antibody affinity, antibody-antigen complex structure, and developability properties. Closely collaborate with drug discovery teams to contribute to the Roche large molecule portfolio, solving unique and challenging protein design and engineering tasks. Contribute to and drive publications and present scientific findings at internal/external venues. Who you are PhD degree in Computational Biology, Structural Biology, Computer Science, Physics or related disciplines, or a MS degree in the above disciplines with 3+years of industry research experience. Demonstrated experience with Python and deep learning libraries such as Pytorch and/or TensorFlow and/or JAX. Demonstrated research experience, including at least one first author publication or equivalent. Publication record and experience contributing to research communities, including conferences like NeurIPS, ICML, ICLR, CVPR, ACL, etc. Strong communication and collaboration skills. Additional desired qualifications: Experience working with data from biology, immunology or related disciplines. Experience with antibody structure, function, and sequence data. Public portfolio of computational projects (available on e.g. GitHub). Relocation benefits are available for this job posting. The expected salary range for this position based on the primary location of California is $147,600, - $274,000. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Benefits #ComputationCoE #tech4lifeComputationalScience #tech4lifeAI Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants . #J-18808-Ljbffr

Machine Learning Engineer, AI/ML for Drug Discovery Join to apply for the Machine Learning Engineer, AI/ML for Drug Discovery role at Atomwise Machine Learning Engineer, AI/ML for Drug Discovery Join to apply for the Machine Learning Engineer, AI/ML for Drug Discovery role at Atomwise About Atomwise: Atomwise is a TechBio company leveraging AI/ML to revolutionize small molecule drug discovery. The Atomwise team invented the use of deep learning for structure-based drug design; a core technology of Atomwise's best-in-class AI discovery and optimization engine, which is differentiated by its ability to find and optimize novel chemical matter. The company's belief is that structurally novel chemical matter increases the likelihood of developing first-in-class and best-in-class medicines that have the potential to transform patient care. About Atomwise: Atomwise is a TechBio company leveraging AI/ML to revolutionize small molecule drug discovery. The Atomwise team invented the use of deep learning for structure-based drug design; a core technology of Atomwise's best-in-class AI discovery and optimization engine, which is differentiated by its ability to find and optimize novel chemical matter. The company's belief is that structurally novel chemical matter increases the likelihood of developing first-in-class and best-in-class medicines that have the potential to transform patient care. Atomwise has extensively tested its discovery and optimization engine, delivering hit ID success in over 230 academic and collaboration projects-to-date that cover a wide breadth of protein classes and numerous "hard-to-drug" targets. Atomwise is building a pipeline of small-molecule drug candidates with first-in-class and best-in-class potential in immunology. The Role: We seek a highly motivated and creative Machine Learning Engineer to join our growing team. You will be at the forefront of developing and applying advanced machine-learning models to accelerate the discovery of novel therapeutics. Your work will directly impact the development of innovative AI-driven drug discovery platforms. This role offers the opportunity to work on challenging problems at the intersection of machine learning, chemistry, and biology, with access to extensive datasets and state-of-the-art computational resources. Responsibilities: Productionize novel deep learning tools for molecular property prediction, design and optimization, and virtual screening. Design and execute experiments to evaluate the performance of experimental models and improve training and inference time/cost. Conduct in-depth analyses of model outputs and performance metrics to identify areas for improvement. Collaborate with cross-functional teams of software engineers, chemists and biologists to integrate ML models into drug discovery pipelines. Stay up-to-date with the latest advancements in machine learning and computational chemistry, and integrate them into Atomwise ML models. Maintain and extend our scalable and efficient machine learning frameworks for at-scale use by drug discovery teams. Qualifications: Masters or higher in Computer Science, Machine Learning, Computational Chemistry, or a related field. Two or more years of industry experience in productionizing machine learning models for distributed training and inference. Proficiency in designing and implementing novel machine learning frameworks in PyTorch. Strong problem-solving and analytical skills, with a demonstrated ability to conduct independent research. Experience with collaborative software engineering and developing high quality, maintainable, well-documented code in a large codebase. Experience with machine learning models of chemical systems is preferred. Familiarity with cheminformatics tools and libraries (e.g., RDKit) is a plus. Compensation & Benefits Competitive salary, commensurate with experience Stock compensation plan - you'll be an Atomwise co-owner Platinum health, dental, and vision benefits for you and your dependents 401(k) retirement plan with generous company match (up to 4%) Flexible paid time off (PTO), 13 paid holidays, and wellness breaks for employees to spend time with their loved ones and recharge Health Savings and Flexible Spending Account options to help save money on healthcare, daycare, and commuting Employee Assistance Program (EAP) and Pet Insurance Funding for professional development and conference attendance Flexible work schedule Generous paid parental leave Atomwise is an equal opportunity employer and strives to foster an inclusive workplace. We are a TechBio company leveraging AI/ML to revolutionize small-molecule drug discovery, and we know that we need a diverse team to develop medicines that serve diverse populations. Accordingly, Atomwise does not make any employment decisions (including but not limited to, hiring, compensation, and promotions) on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, veteran status, disability status, or any other characteristics protected by applicable federal, state, and local law. We strongly encourage people of diverse backgrounds and perspectives to apply. The base salary for this position is $175,000- $60,000. Pay is determined by multiple factors including, but not limited to, a candidate's geographical location, experience and skills. We're considering all levels of experience for this position. Seniority level Seniority level Entry level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Referrals increase your chances of interviewing at Atomwise by 2x Get notified about new Machine Learning Engineer jobs in San Francisco, CA . 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