ML/AI Platform Engineer - Evinova

Introduction to role

Are you ready to be part of the future of healthcare? Are you able to think big, be ambitious and harness the power of digital and AI to solve longstanding life sciences challenges? Then Evinova, a new healthtech business part of the AstraZeneca Group might be for you! Transform billions of patients’ lives through technology, data and innovative ways of working. You’re disruptive, decisive and entrepreneurial. Someone who’s excited to use technology to improve patients’ health. We’re building a new healthtech 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. Smart risks and quick decisions come together to accelerate innovation across the life sciences sector. Be part of a team with varied strengths that pushes the boundaries of science by digitally empowering a deeper understanding of the patients we’re helping. Launch innovative 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.

Accountabilities

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 lead 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 quintessential 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 an ML/AI Engineer on our team, you will design and scale innovative AI capabilities for our products and operations. Specializing in AWS Services (such as Sagemaker, Bedrock, Lex, OpenSearch, etc.) and modern AI platforms and stacks, you will utilize the latest frameworks and methodologies in Generative AI to create real business value. Your expertise in AWS cloud infrastructure, DevOps, Foundation Models (FMs), prompt engineering, RAG, and LLMOps tools like DSPy, Letta, LlamaIndex, and LangChain will be pivotal in enhancing our AI capabilities and driving innovation.

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.

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 cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, analytics, and predictive capabilities for the systems we build, manage and govern.

ML/AI Cloud Operations and Engineering

- Design and scale GenAI applications using AWS Services and innovative GenAI stacks and frameworks.
- Ensure AI projects have principled and methodical validation pathways that adhere to our platform development lifecycle -- so we either fail fast or get to market as efficiently and quickly as possible.
- Maintain and teach advanced understanding of constantly evolving frameworks such as DSPy, Letta (formerly MemGPT), LlamaIndex, LangChain, Vector DBs, RAG (and constantly evolving innovations such as Cache-Augmented Generation (CAG)) to enhance AI capabilities across engineering and science organizations.
- Apply and teach sophisticated prompt engineering techniques to improve AI model interactions and outputs, and promote “prompts as programs” philosophy and management/governance implications.
- Embed deeply within and across product, design, science and business teams to build AI capabilities that have tangible and quantifiable product and business impact.

Personal Attributes:

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

Essential Skills/Experience

- Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture and development process (AWS TypeScript CDK, Argo CD, Helm, Kubernetes).
- Expertise in RAG methodologies and AWS Bedrock, Sagemaker, Lex and OpenSearch for developing AI and automation solutions.
- Expertise and vigilance of the latest GenAI frameworks and tools like DSPy, Letta, LlamaIndex, and LangChain.
- Advanced coding skills in relevant programming languages (Python/JavaScript/TypeScript) and frameworks.
- Similar CI/CD cloud operations skills as a Cloud Solutions Architect or DevOps engineer, with additional expertise in data science and ML/AI engineering.
- Minimum of 5 years in ML/AI engineering.
- Proven track record of designing and implementing ML/AI end-to-end workflows.
- Demonstrated ability to identify real business and product opportunities and implement cutting-edge technologies and methodologies in production environments to drive tangible and quantifiable product and business value.
- Experience working with diverse teams to achieve product and organizational objectives through automation.
- HS Diploma and 8 years of experience in Engineering/IT solutions OR BA/BS Degree and 5 years of experience or equivalent capabilities.

When we put unexpected teams in the same room, we unleash 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.

AstraZeneca is where creativity meets purpose! We embrace technology to reimagine healthcare's future. Our collaborative culture fuels innovation while making a real difference in patients' lives. Join us on this exciting journey!

Ready to make an impact? Apply now!

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.