Research Software Engineer, AI-Enriched Simulation
IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today’s most complex challenges, whether it’s discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.Your Role and ResponsibilitiesIBM Research, in the UK, is seeking high calibre candidates with a proven track record in applied research and development, research that makes a difference. We offer a stimulating research environment comprising multi-disciplinary teams with diverse expertise working on challenging projects in a world-class research organization. We have access to cutting-edge experimental environments and strong ties with industrial, national, and academic research labs around the globe. You will want to be part of a team that is making a difference on how we can accelerate discovery using advanced technology.
The position requires to commute to either Daresbury or Hursley, 2 times a week.
We are pleased to advertise an opening in our AI-Enriched Simulation team. This role is for a generalist who is passionate about understanding and advancing the role AI and machine learning can play in the advancement of simulation technologies. This could be through advanced steering of simulations, building new powerful recommender systems, or the building of accurate data-driven models for property prediction and analysis. We are particularly looking for experience in the interface of AI/ML with the physical sciences, especially chemistry and materials.
Your Role and Responsibilities
Modelling and Simulation remains a key technology for scientific discovery. In addition to embracing new paradigms for calculation, for example cloud and quantum, IBM are actively pursuing the use of AI to accelerate modelling and simulation workflows. The foundational technology – simulation team have three specific focus areas:
1. Simulation tech for science; Using the latest technology and methodologies to develop and enable cutting edge scientific simulations
2. AI enriched simulation: Driving differentiation through the use of AI to accelerate time to insight by both accelerating individual simulations through the use of data-driven surrogate modelling, and the intelligent orchestration of simulation campaigns through Bayesian optimization
3. Simulation workflow technology – developing differentiated workflow technology to integrate the latest simulations with the latest AI enrichment in a hybrid cloud infrastructure.
Your role in the AI Enriched Simulation team would be to use your software engineering prowess to help enable the consumable delivery of the research being delivered in this focus area. Particular focus would be on the building and delivery of API based service capabilities which allow the separation of concerns between those consuming the research and those developing new research. Required Technical and Professional Expertise
- Ability to identify fundamental problems from real-world cloud use-cases and to design, build and validate successful cloud-focused solutions.
- Ability to analyse the performance of modelling and simulation workflows to identify and remove bottlenecks
- Ability to demonstrate and evaluate systems/software via experimental method, particularly through hands-on creation of prototypes. For example, configuring large-scale server/networking/storage infrastructures; deploying research prototypes within production-grade HPC/Cloud infrastructures; deep contribution or ownership of an opensource cloud middleware framework.
- Strong communication skills and the ability to collaborate effectively within local team
- Excellent command of the English language, both verbal and written
Preferred Technical and Professional Expertise
Any of the following additional skills are highly desirable.
• Experience developing software with Python, and related ML frameworks such as PyTorch and their ecosystems of tools and libraries.
• Experience with cloud-native environments, such as AWS (S3, lambda, CloudTrails, etc) or other cloud vendors.
• Experience with Kubernetes.
• Experience with DevOps in a Software as a Service (SaaS) environment.
• Experience in a data science or data engineering environment.
• Experience with AI/ML, or High Performance Computing (HPC).
• Experience in scientific research or software engineering for research.