Senior ML/AI Operations Engineer - Evinova

Job Title: Senior ML/AI Operations Engineer - Evinova
Location: Gaithersburg, MD

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe. 

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices 3 days a week. Our head office is purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects. 

Are you ready to be part of the future of healthcare? Can you think big, be bold, and harness the power of digital and AI to tackle longstanding life sciences challenges?  Then Evinova, a global health tech business might be for you!  

Transform patients’ lives through technology, data, and innovative ways of working. You’re disruptive, decisive, and transformative. Someone excited to use technology to improve patients’ health. We’re building a new Health-tech business – Evinova, a fully-owned subsidiary of AstraZeneca Group.

Evinova delivers market-leading digital health solutions that are science-based, evidence-led, and human experience-driven. Thoughtful 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 pioneering digital solutions that improve the patients’ 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. 

Introduction to Role:

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed team 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.

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).

As a Senior ML/AI Operations Engineer for clinical trial design, planning, and operational optimization on our team, you will lead the development and management of MLOps systems for our trial management and optimization SaaS product. You will collaborate closely with data scientists to transition projects from embryonic research into production-grade AI capabilities, applying advanced tools and frameworks to optimize model deployment, governance, and infrastructure performance.

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

Accountabilities:

Operational Excellence

• Lead by example in creating high-performance, mission-focused and interdisciplinary teams/culture founded on trust, mutual respect, growth mentalities, and an obsession for building extraordinary products with extraordinary people.
• 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 enhance 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

• Develop and manage MLOps/AIOps/LLMOps systems for clinical trial design, planning and operational optimization.
• Partner closely with data scientists to shepherd projects from embryonic research stages into production-grade ML/AI capabilities.
• Leverage and teach modern tools, librari