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 Responsibilities
The work location for this role is either Daresbury Labs or Hursley Labs for a minimum of 2 days a week.
As a member of our IBM Research team, your responsibilities will include developing, operationalizing, and scaling our toolkits and modelling ecosystem, working with complex materials datasets and large climate datasets for discovery and making them consumable in science and business.
Required Technical and Professional Expertise
Undergraduate degree in Computer Science, Maths, Physics, or Engineering.
Demonstrated software development experience in scientific computing environment.
Proven experience in collaborative software projects—for example collaborating with others in an open-source project or developing tools for a research team.
DevOps tools for collaborative software development.
Experience in building application frameworks, especially solid understanding of API design patterns.
Experience in building data ingest and data transformation infrastructure.
Data science and machine learning experience including data cleansing, training, and evaluating machine learning models, especially application know-how in natural language processing and geospatial analytics.
Skilled in Jupyter notebooks and the use of standard Python libraries (pandas, numpy, sci-kit learn) for prototyping and application development.
Demonstrated ability to organize, prioritize, and multi-task in a fast paced, changing, and agile development environment to meet deadlines.
Effective written and verbal communication and interpersonal skills.
Preferred Technical and Professional Expertise
Postgraduate degree in Computer Science, Maths, Physics, or Engineering
Experience with AI/ Machine Learning, Quantum Computing, or High Performance Computing (HPC).
Experience in scientific research or software engineering for research.
Experience in cloud native application design and development leveraging microservices and cloud native patterns, workflow, event-driven architecture
Experience with cloud-native environments, such as AWS (S3, lambda, CloudTrails, etc) or other cloud vendors.
Experience building and deploying across multiple cloud environments
Experience using containerised cloud platforms such as Kubernetes or OpenShift
Working experience building workflows and AI models in platforms such as Ray, Pytorch, MLFlow, etc.
Experience working with materials datasets and models (e.g., metal-organic frameworks (MOFs) materials, and catalysts for carbon capture and conversion).
Experience working with climate data and models, including climate impacts (e.g. flood, drought, wild fire, diseases), and standard climate data formats (netcdf, grib)
Experience working with nosql databases
Experience creating (or at least using) REST-APIs and SDKs.