$164K – $240KSeniorFull Time
Rescale is pioneering the future of engineering and scientific discovery. As the leader in digital engineering, we’re transforming how products are developed—through intelligent automation, applied AI, data management, and the integration of the world’s largest network of engineering and R&D applications. Joining Rescale means becoming part of a diverse, collaborative, and mission-driven team that’s unlocking faster innovation across industries like aerospace, energy, life sciences, and manufacturing. We’re solving complex challenges that traditional HPC can’t—and we’re seeking passionate, curious minds to help build the next wave of breakthroughs.
We're expanding the modeling and simulation workflow by integrating data management and AI development into a single platform experience. We accelerate engineering breakthroughs by delivering a multi-cloud platform that orchestrates modeling and simulation on top of the most common CAE software and latest hardware available.
We enable our customers to:
Get products to market faster by replacing the bottleneck of fixed on-premise hardware with unlimited and elastic cloud capacity
Automate their full HPC technology stack, including lifecycle management of simulation software & licenses (catalog of 300+ ISV and open-source tools)
Gain complete economic visibility, cost control, and optimization across projects and teams running on multi-cloud infrastructures
We're looking for a Principal Product Manager with expertise in data management and AI workflows to define and deliver the next generation of our platform capabilities. You'll deeply understand customer challenges, develop strategic plans, and collaborate with engineering and go-to-market teams to ensure both product delivery and commercial success.
This role requires someone who understands the convergence of traditional physics simulation with modern AI approaches, particularly how machine learning models can accelerate or replace computationally expensive simulations. You'll be the CEO of your product area, making data-driven decisions while staying intimately connected with key customer personas in engineering and R&D.
Product Strategy & Roadmapping: Define and own product roadmaps that prioritize capabilities driving customer value and business growth. Balance traditional simulation workflows with emerging AI-accelerated approaches.
Customer Engagement: Partner directly with engineering teams and data scientists to understand their computational challenges. Identify opportunities where AI can dramatically reduce simulation time or enable new types of analysis.
Product Development: Define and scope new capabilities that bridge physics-based modeling and machine learning. Work with engineering to deliver hybrid workflows that combine the accuracy of traditional simulation with the speed of AI models.
Technical Leadership: Evangelize the integration of surrogate models and physics-informed neural networks into engineering workflows. Guide customers on when to use traditional HPC versus AI-accelerated methods.
Ecosystem Integration: Build partnerships and integrations with leading AI infrastructure providers and simulation software vendors. Stay current on GPU-accelerated computing trends and foundation models for scientific computing.
Business Ownership: Own the full lifecycle of your product area - from investment decisions and prioritization to delivery, field enablement, and commercial success.
6+ years of product management experience, preferably in B2B enterprise software
Bachelor's degree in engineering, physics, computer science, or related technical field
Strong track record of shipping high-impact products
Experience with scientific computing, simulation, or computational modeling
Understanding of machine learning applications in engineering and science
Familiarity with GPU computing and modern AI infrastructure
Excellent problem-solving and communication skills
Self-starter comfortable operating in ambiguity
Outcome-driven mindset with strong analytical capabilities
Experience with physics-informed machine learning or surrogate modeling techniques
Knowledge of foundation models and their application to scientific computing
Familiarity with GPU-accelerated simulation frameworks and AI model serving platforms
Understanding of MLOps practices for scientific and engineering applications
Experience with CAE software and engineering simulation workflows
Background in computational physics, computational fluid dynamics, or finite element analysis
Hands-on experience with AI model training and deployment pipelines
Track record working with R&D teams in aerospace, automotive, or semiconductor industries
You'll work at the intersection of:
Traditional HPC and physics-based simulation
Machine learning model development and deployment
GPU computing and acceleration technologies
Cloud-native AI platforms and infrastructure
Scientific data management and visualization
Model validation and uncertainty quantification
Hybrid physics-AI workflows
This is an opportunity to shape how Fortune 500 engineering teams leverage the convergence of physics simulation and AI to achieve 100-1000x speedups in their design and analysis workflows. You'll help define the future of engineering simulation, where AI models trained on physics data can provide near-instant insights that previously required hours or days of computation.
You'll work with customers pushing the boundaries of what's possible - from training surrogate models that replace expensive CFD simulations to deploying physics-aware neural networks that maintain accuracy while dramatically reducing computational cost.
Rescale is an equal opportunities employer and welcomes applications from all qualified persons regardless of their race, sex, disability, religion/belief, sexual orientation or age. As part of our standard hiring process for new employees, employment with Rescale will be contingent upon successful completion of a comprehensive background check. Here at Rescale, we are committed to being transparent in our policies around candidate privacy. For more details on the information Rescale collects in your application, please view the Rescale Applicant Privacy Policy here.
