An innovate start-up is hiring a Process Development Engineer to work with industrial customers to support the deployment of AI-driven solutions in technical and operational environments.
This is a cross-functional role that combines engineering, customer collaboration, data analysis, and technical problem-solving. You'll work with a range of stakeholders to understand operational challenges, analyze process and production data, develop models and workflows, and help drive improvements using the company's platform
.
The ideal candidate is comfortable engaging with technical teams, working with data and analytical tools, and translating technical findings into practical business outcomes
Internally, you'll act as a technical subject matter expert and advocate for customer needs across manufacturing and process-related initiatives
Externally, you'll support enterprise customers by partnering with engineering and operations teams to maximize value from the platform, whether by improving existing workflows or helping implement new solutions.
In collaboration with Sales, Product, and Engineering, you'll also contribute to identifying new use cases and shaping future platform capabilities
Customer Engagement & Project Delivery
- Partner with customers to support deployment and adoption of platform solutions
- Lead onboarding and implementation efforts across technical and operational environment
- Build relationships with engineering, operations, and leadership stakeholders
- Identify opportunities for operational improvement and data-driven insights
- Translate customer challenges into actionable technical solutions and product feedback
Technical Analysis & Problem Solving
- Analyze operational and process datasets to identify trends, bottlenecks, and optimization opportunities
- Develop analytical models, simulations, and workflows using Python
- Collaborate with product and engineering teams to improve platform functionality
- Communicate technical findings to both technical and non-technical audiences
- Support troubleshooting and continuous improvement initiatives in complex operational
Required Qualifications
- 5–7 years of experience in manufacturing, process engineering, or related industrial environments.
- Experience developing and applying first-principles (physics-, chemistry-, and biology-based) models of bioprocesses and biologics manufacturing operations.
- Candidates should have demonstrated experience building mechanistic models from fundamental transport, reaction, thermodynamic, kinetic, and cellular processes rather than purely empirical or machine-learning approaches.
Examples may include:
- Upstream bioprocess modeling (cell culture, microbial fermentation, metabolic and growth kinetics, nutrient consumption, product formation).
- Downstream process modeling (chromatography, filtration, UF/DF, precipitation, mixing, mass transfer, adsorption, and purification operations).
- Digital twins and process simulations for biologics manufacturing facilities.
- Scale-up and scale-down modeling based on transport phenomena and bioprocess fundamentals.
- Mechanistic modeling for process optimization, control, technology transfer, capacity planning, or process development.
Preferred Qualifications
- Experience implementing models in MATLAB, Python, gPROMS, Aspen Custom Modeler, COMSOL, Julia, or similar platforms.
- Experience supporting commercial manufacturing, process development, or Manufacturing Science and Technology (MSAT) teams.
- Ability to derive, calibrate, validate, and interpret mechanistic models using experimental and manufacturing data.
US
