Evinova delivers market-leading digital health solutions that are science-based, evidence-led and human experience-driven. Smart risks and quick decisions come together to accelerate innovation across the life sciences sector. Be part of a diverse team that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we’re helping. Launch game-changing digital solutions that improve the patient experience and deliver better health outcomes. Together, we have the opportunity to combine deep scientific expertise with digital and artificial intelligence to serve the wider healthcare community and create new standards across the sector.  

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed team of battle-tested and proven SaaS ML/AI developers and operators that will spearhead the design, creation, and operational excellence of our entire ML/AI data and computational AWS ecosystem to catalyze and accelerate science led innovations through our pharmaceutical clinical SaaS products.  

This team is responsible and accountable for the design, implementation, deployment, health and performance of all algorithms, models, ML/AI operations (MLOps, AIOps, and LLMOps) and Data Science Platform. We manage ML/AI and broader cloud resources, automating operations through infrastructure-as-code and CI/CD pipelines, and ensure best-in-class operations – striving to push even beyond mere compliance with industry standards such as Good Clinical Practices (GCP) and Good Machine Learning Practice (GMLP).  

On the human side of the equation, our team forges deep relationships across broader engineering, design, product and science organizations and are quite essential and consummate interdisciplinary teammates and collaborators that can build on our deep heritage within global pharmaceutical clinical trials to drive State-of-the-art (SOTA) AI product experiences with tangible and quantifiable product and business operations impact. 

As the ML/AI Platform Architect on our team, you will architect and oversee the global cloud ML/AI infrastructure that underpins our entire ML/AI value proposition. You will design, implement, and manage scalable cloud solutions using AWS services while establishing ML/AI governance frameworks, automating infrastructure with tools like AWS CDK and Projen, and conducting cost-benefit analyses of foundation models to drive strategic decisions across the organization. 

This position requires a deep understanding of cloud-native ML/AI Ops methodologies and technologies, AWS infrastructure, State-of-the-art (SOTA) Foundation Models and AWS GenAI Services, and the unique demands of regulated industries, making it a cornerstone of our success in delivering impactful solutions to the pharmaceutical industry. 

Role & Team Key Responsibilities: 

Operational Excellence 

• Lead by example in creating high-performance, mission-focused and interdisciplinary teams/culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people. 
• Lead by example in using reactive firefighting to drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.  
• Design and implement resilient cloud ML/AI operational capabilities to maximize our system A-bilities (Learnability, Flexibility, Extendibility, Interoperability, Scalability). 
• Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, comprehensive analytics, and predictive capabilities at the tree-and-forest level of our ML/AI systems, workloads and processes. 

ML/AI Cloud Operations and Engineering 

• Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment. 
• Establish governance frameworks for ML/AI infrastructure management and ensure compliance with industry best practices. 
• Ensure principled and methodical validation pathways and a Well Architected Framework for Embryonic Research (WAFER) similar to and building on AWS’s Well Architected Framework (WAF) for all early stage product and operational GenAI PoC’s across the organization. 
• Oversee ML/AI related Kubernetes (k8s) cluster management and provide expertise on alternative ML/AI workflow orchestration options such as Argo vs Kubeflow, and ML/AI data pipeline creation, management and governance with tools like Airflow. 
• Employ AWS CDK (TypeScript), Projen, and Argo CD to automate infrastructure deployment and management. 
• Help set the strategy and manage the tactical balance between framework and platform experimentation and democratization with standardization and centralized management and governance 
• Conduct cost-benefit analyses and formal processes for selection and utilization of foundation models, evaluating their architectures, performance, and costs. 
• Work with multiple teams to ensure that the platform meets organizational needs and scales effectively. 

Personal Attributes:

• Customer-obsessed and passionate about building products that solve real-world problems.
• Highly organized and detail-oriented, with the ability to manage multiple initiatives and deadlines.
• Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive. 

Skills: 

• Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture. 
• Expert in Typescript, AWS CDK, Projen, and Argo CD and other Cloud Infrastructure CI/CD Tools 
• Extensive experience in managing Kubernetes clusters for ML workflows. 
• Solid understanding of foundation models and their applications in ML/AI solutions. 
• Strong background in AWS DevOps practices and cloud architecture.  
• Deep knowledge of AWS services (Bedrock, Sagemaker, EC2, S3, RDS, Lambda, etc) and hands-on design and implemention cloud systems (microservices architecture, API design, and database management (SQL/NoSQL)) 
• Experience with monitoring and optimizing cloud infrastructure for scalability and cost-efficiency. 
• Ability to collaborate effectively with engineering, design, product, science and security teams. 
• Strong written and verbal communication skills for reporting and documentation. 

Experience: 

• Minimum of 10 years in cloud infrastructure design and management roles. 
• Previous experience as an AWS DevOps or Cloud Architect with a focus on ML/AI. 
• Demonstrated ability to manage large-scale, complex projects across an organization. 
• Proven experience in conducting performance and cost analyses of AWS infrastructure and ML/AI models. 

Education: 

• HS Diploma and 8 years of experience in Engineering/IT solutions OR BA/BS Degree and 5 years of experience or equivalent capabilities. 
• Preferred Education: M.S. or PhD in Computer Science or related field.

In-Office Expectation:

When we put unexpected teams in the same room, we fuel bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why Evinova (AstraZeneca)?

Evinova draws on AstraZeneca’s deep experience developing novel therapeutics, informed by insights from thousands of patients and clinical researchers. Together, we can accelerate the delivery of life-changing medicines, improve the design and delivery of clinical trials for better patient experiences and outcomes, and think more holistically about patient care before, during, and after treatment.  We know that regulators, healthcare professionals, and care teams at clinical trial sites do not want a fragmented approach. They do not want a future where every pharmaceutical company provides its own, different digital solutions. They want solutions that work across the sector, simplify their workload, and benefit patients broadly. By bringing our solutions to the wider healthcare community, we can help build more unified approaches to how we all develop and deploy digital technologies, better serving our teams, physicians, and ultimately patients.  Evinova represents a unique opportunity to deliver meaningful outcomes with digital and AI to serve the wider healthcare community and create new standards for the sector. 

Interested? Come and join our journey.

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.