Senior Process Data Scientist/Development Engineer - AI-Driven Bioprocess Innovation Help reinvent how biopharmaceutical processes are designed, scaled, and optimized.
A North American AI technology company is looking for a
Senior Process Development Engineer
to bring deep bioprocess and mechanistic modeling expertise to a new generation of AI-powered manufacturing technology.
You'll work directly with
leading pharmaceutical and biotechnology companies
to solve complex process challenges—from process development and scale-up to technology transfer and commercial manufacturing. You'll combine
first-principles modeling, process engineering, and AI
to turn real manufacturing data into better decisions, faster optimization, and measurable operational impact.
This is an opportunity to move beyond traditional process simulation and help shape how
AI-driven digital twins are applied to biopharmaceutical manufacturing.
What You'll Do Drive Process Innovation
Partner directly with pharmaceutical and biotechnology customers to solve complex
process development and manufacturing challenges
Work with process engineers, scientists, MSAT, R&D, and operations teams to identify opportunities for optimization
Translate real-world manufacturing problems into
modeling strategies, technical solutions, and product capabilities
Lead projects from initial process assessment through implementation and measurable customer impact
Build the Models Behind AI-Driven Manufacturing
Develop and apply
first-principles, mechanistic, dynamic, and hybrid models
for biopharmaceutical processes
Analyze experimental and manufacturing data to understand process behavior, identify bottlenecks, and uncover optimization opportunities
Build dynamic simulations that combine
fundamental engineering principles with data-driven and AI approaches
Apply models to
process optimization, scale-up/scale-down, technology transfer, process control, and manufacturing improvement
Develop, calibrate, validate, and interpret models using experimental and plant/manufacturing data
What You Bring
7-10+ years
of experience in pharmaceutical or biotechnology manufacturing, process development, MSAT, or a closely related field
Experience working across
laboratory, pilot, or commercial-scale operations
Strong foundation in
first-principles and mechanistic modeling
Ability to translate fundamental principles—such as
mass/energy balances, transport phenomena, reaction kinetics, thermodynamics, or biological kinetics —into practical process models
Experience applying models to real process-development or manufacturing problems
Strong communication skills and the ability to work directly with technical customers and cross-functional teams
Relevant Technical Experience Your background may include:
Upstream:
cell culture, fermentation, growth kinetics, metabolic modeling, nutrient consumption, product formation
Process modeling:
digital twins, dynamic simulation, scale-up/scale-down modeling, process optimization, process control
Preferred Qualifications
Experience with
Python, MATLAB, gPROMS, Aspen Custom Modeler, COMSOL, Julia , or similar modeling platforms
Experience in
commercial manufacturing, MSAT, technology transfer, or process validation
Experience connecting models with experimental, pilot, or manufacturing data
Experience with digital twins, hybrid modeling, or AI-enabled process optimization
PhD or advanced degree in
Chemical Engineering, Biochemical Engineering, Biotechnology, or a related discipline
is a plus
Why This Role This isn't a traditional process engineering role.
You'll sit at the intersection of
biopharmaceutical manufacturing, mechanistic modeling, and AI , working on technology that can fundamentally change how complex manufacturing processes are understood and optimized.
You'll have the opportunity to:
Work directly with
leading pharmaceutical companies
Solve technically challenging, high-value manufacturing problems
Apply your process expertise to
next-generation AI technology
Influence both customer solutions and the evolution of the product
Work with smart colleagues in a well funded start-up
Help move bioprocess modeling from analysis into
real-time, actionable manufacturing decisions
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