Job Description

The Onyx Research Data Tech organization is GSK’s Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.

Onyx is a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:?

Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics”?

Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent?

Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time?

At GSK we see a world in which advanced applications of?AI will allow us to develop transformational medicines using the power of genetics, functional genomics, and?machine?learning.? AI will also play a role in how we diagnose and use medicines to enable everyone to do more, feel better, and live longer.?? It is an ambitious?vision?that will require the development of products at the cutting edge of?AI and Machine?Learning. We're looking for a highly skilled?AI/ML Platform?Engineer?to help us make this?vision?a reality.  

Our AI/ML?Platform Engineering team is building a first-in-class platform of tools and services covering MLOps/DevOps across Cloud and High-Performance Computing. Our goal is to decrease development time and raise the quality bar on engineering across AI/ML teams and products. 

The AI/ML?team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career from day one, supporting individuals in dedicating 20% of their time towards personal development. 

Key responsibilities for this role include:

Design, develop, test, document and maintain platform services, tools, and infrastructure? 

Continuously scale and enhance operational efficiencies around platform’s CI/CD capabilities? 

Work closely with engineers, researchers, and other science domain experts on productionizing AI/ML models and pipelines? 

Drive and maintain development standards and processes across the team and wider organization? 

Stay up to date on the latest?leading technologies in the AI/ML?software ecosystem ? 

Why you?

Basic Qualifications:

We are looking for professionals with these required skills to achieve our goals:

BS or MS in Computer Science or a related technical field, or equivalent experience 

3+ years of industry and/or academic experience in software engineering 

Experience in?designing and implementing web APIs and packaged tools in Python 

Knowledge of Cloud Computing, distributed systems and C/CD

Familiarity with Kubernetes and/or Docker 

Familiarity with ML frameworks such as PyTorch, TensorFlow, or Sci-kit Learn 

Preferred Qualifications:

If you have the following characteristics, it would be a plus:

Experience working in a highly regulated industry such as Healthcare 

Experience in the AI/ML?and Big Data space 

Experience in workflow orchestration with tools such as Argo Workflow, Kubeflow, Airflow, etc. 

Experience with Cloud CI/CD infrastructure and tools such as Azure DevOps and CloudBuild 

Experience with Infrastructure as Code tools such as Terraform, Ansible, and Packer 

Knowledge of the wider CNCF ecosystem around build, deployment, orchestration, and monitoring 

Familiarity with more than one cloud computing environment (AWS, Azure, GCP) 

Familiarity with Event-Driven APIs

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