Rescale provides a global software platform and hardware infrastructure for companies to perform scientific and engineering simulation.

• We provide the largest, most secure, global high performance computing (HPC) footprint seamlessly integrated into an easy-to-use platform built for engineers and scientists. We are disrupting the staid on premise HPC world.
• Not that long ago, we were a team of two, who rendered the Boeing 787 wing on commodity hardware, saving $150M in the process. Now we are a team of 50+ software engineers, computer scientists, and domain experts, helping advanced tech companies bring their complex use cases to the cloud.
• Investors in Rescale include Sam Altman, Jeff Bezos, Richard Branson, Chris Dixon, and Paul Graham, among others.

Rescale is high performance computing built for the cloud. We empower engineers while giving IT security and control. From supersonic jets to personalized medicine, industry leaders are bringing new product innovations to market with unprecedented speed and efficiency. Rescale is a cloud platform delivering intelligent full-stack automation and performance optimization. IT leaders use Rescale to deliver HPC-as-a-Service with a secure control plane to deliver any application, on any architecture, at any scale on their cloud of choice.

We are seeking a highly motivated and experienced _ HPC Engineer, AI and Data _ to join our team.

At Rescale, this means you will work on and impact: 

• Become an expert in the Rescale platform and its application to customer workflows.

• Solve complex HPC AI problems for customers on our platform.

• Integrate cutting-edge AI technologies into CAE workflows. 

• Collaborate with a dynamic and agile development team.

• Engage directly with customers to understand their needs and provide tailored solutions.

• Contribute to the development and enhancement of our AI software products.

• Stay updated with the latest advancements in HPC and AI technologies.

• Participate in code reviews and provide constructive feedback to peers.

What we’re looking for: 

• Advanced degree in Machine Learning, Computer Science, Aerospace Engineering, or a related field (preferably a PhD).

• 5-10 years of industry experience.

• Strong problem-solving skills and self-motivation.

• Software development experience

• Expertise in HPC and applying AI technology to CAE workflows.

• Proficiency in key skills: PyTorch, Modulus, PyG, CAE/CFD/FEA, REST API development, CUDA, Kubernetes, and more.

• Excellent communication and teamwork skills.

• Ability to work independently and manage multiple tasks effectively.

• Passion for continuous learning and professional development.

Rescale is an Affirmative Action, Equal Opportunity Employer.  As part of our standard hiring process for new employees, employment with Rescale will be contingent upon successful completion of a comprehensive background check.   

Problems we are Solving:

• We're building a cloud orchestration framework to execute complex engineering workflows across multiple cloud providers.
• We provide an additional layer of reliability, fault tolerance, and tuning for HPC applications which were not originally designed to run on cloud hardware.
• We are helping engineering companies figure out the best way to incorporate machine learning algorithms into their design lifecycle.

Tech Stack:

• Javascript - React/Angular
• Python - Django Rest Framework
• (Modern) Java - Dropwizard
• Our core infrastructure runs on AWS. The compute clusters we run for customers are created on AWS, Azure, GCP, and IBM in the cloud, along with Bare Metal On-Premises data centers.

Our engineering team is broken up into smaller groups of 5-7 people with a combined full stack skill set. We try to keep meetings to a minimum: there is a daily standup and a weekly task estimation meeting. We have two week release cycles however developers are encouraged to push important features and bug fixes to production as needed. Writing clean, testable code is a point of emphasis and we use GitHub PRs to ensure a minimum quality bar and also to disseminate best practices and spread domain knowledge around.