hackajob is collaborating with GSK to connect them with exceptional tech professionals for this role.

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