Associate Principal Scientist, Deep Learning Engineer within Data-Rich Experimentation (DRE)

Overview

Job Description: Associate Principal Scientist, Deep Learning Engineer within Data-Rich Experimentation (DRE).

Primary Responsibilities

In this role, the candidate will work with a team of scientists identifying, developing, and deploying data-rich technologies to improve process understanding. The role leverages process modeling, machine learning, and other data science approaches to enable process research and development across the Company\'s biologics and vaccines portfolio. The DRE organization develops new data-rich tools to support scientists across process R&D and aims to embed data-intensive technologies into the process development culture. The Associate Principal Scientist solves complex process R&D challenges in an interdisciplinary, collaborative environment via invention, development, and application of cutting-edge process modeling, including novel deep neural network architectures and their combination with physics through hybrid methods. The goal is to elucidate deeper understanding and optimization of processes, driving faster and higher-quality development for diverse medicines and vaccines. The role combines process modeling and deep learning to advance process-focused scientific research, including but not limited to mechanistic, hybrid, or data-driven models for chemical synthesis and isolation, cell culture, fermentation, biomolecule separations; working with pipeline teams to extract insights from experimental data for manufacturing design; using ML-assisted experiment design to accelerate development; applying physics-based and hybrid models to guide scale-up and technology transfer; developing new hybrid ML frameworks and integrating them with physics-based models; and collaborating with IT for automated scaling, training, and deployment of models. A strong background in machine learning with emphasis on modeling and manufacturing process development is required.

The candidate should demonstrate excellent interpersonal, communication, and collaboration skills, embrace diversity and inclusion, and work effectively in a dynamic, integrated, multidisciplinary team. The candidate should demonstrate a track record of scientific innovation, publications, and presentations, and be able to build trusted partnerships across stakeholder networks. The group welcomes diverse problem solvers dedicated to creating life-changing medicines and vaccines.

Education Minimum Requirement

• A Ph.D. in Engineering, Biology, Chemistry or a closely-related field with at least 3 years of industrial/pharmaceutical experience
• A M.S. in Engineering, Biology, Chemistry or a closely-related field with at least 5 years of industrial/pharmaceutical experience
• A B.S. in Engineering, Biology, Chemistry or a closely-related field with at least 7 years of industrial/pharmaceutical experience

Required Experience and Skills

• Background and experience in process modeling, scientific machine learning, deep learning, and technology deployment.
• Expertise in Python with hands-on experience in deep learning frameworks and libraries (PyTorch, JAX, TensorFlow, or similar).
• High motivation for novel technology development; passion for modernizing chemical and bioprocess development practices.
• Excellent communication skills, creativity, adaptive problem-solving, and interpersonal skills for delivering complex technical solutions in a dynamic cross-functional environment.
• Demonstrated scientific expertise evidenced through impactful journal publications and/or conference presentations.

Preferred Experience and Skills

• Experience in developing novel process models for dynamical systems, process control, or digital twins for chemical or biological systems through physics-based, mechanistic, or hybrid frameworks.
• Background in laboratory chemical or biochemical research, cell culture, or fermentation process design, development, or optimization; experience applying or developing data-rich technologies to extract insights from complex laboratory data.
• Familiarity with MLOps practices and workflows (automated training, documentation and monitoring, deployment and integration) and ability to collaborate with IT for deployment at scale.
• Experience in new technology development with understanding of technology adoption frameworks and a track record of technology change management.

EEO statement: As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other legally protected characteristics. We comply with affirmative action requirements where applicable.

Current Employees apply via the company site. Current Contingent Workers apply via the company site.

US and Puerto Rico Residents Only: Our company is committed to inclusion. Please click here if you need an accommodation during the application or hiring process.

San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records in compliance with the San Francisco Fair Chance Ordinance.

Los Angeles Residents Only: We will consider all qualified applicants in a manner consistent with local laws, including the City of Los Angeles Fair Chance Initiative for Hiring Ordinance.

Hybrid Work Model: U.S. employees in office-based positions will follow a hybrid model (three on-site days per week, Friday remote) unless business needs require otherwise. This does not apply to remote roles, field-based roles, or roles under a collective bargaining agreement unless stated.

Salary Range: $139,600.00 - $219,700.00. The salary falls within this range based on factors including education, experience, location, and business needs. The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

Benefits: Comprehensive medical, dental, vision, retirement (401(k)), paid holidays, vacation, and sick days. More information is available on the company compensation and benefits page.

Application: Apply at the company careers site. The posting end date is listed on the job posting.

Travel and Other Details: Travel requirements, flexible work arrangements, relocation, visa sponsorship, and other details are described in the job posting as applicable.

Job Posting End Date: 10/3/2025

Requisition ID: R