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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 Cloud 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, libraries, frameworks and standard methodologies to design, validate, deploy and monitor data pipelines and models in production (examples include, but are not limited to AWS Sagemaker, MLflow, CML, Airflow, DVC, Weights and Biases, FastAPI, Litserve, Deepchecks, Evidently, Fiddler, Manifold). Establish systems and protocols for entire model development lifecycle across a diverse set of algorithms, conventional statistical models, ML and AI/GenAI models to ensure best-in-class Machine Learning Practice (MLP). Enhance system scalability, reliability, and performance through effective infrastructure and process management. Ensure that any prediction we make is backed by deep exploratory data analysis and evidence, interpretable, explainable, safe, and actionable. Personal Attributes: Customer-obsessed and passionate about building products that solve real-world problems. Highly organized and meticulous, with the ability to manage multiple initiatives and deadlines. Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive. Essential Skills/Experience: HS Diploma or GED Minimum of 2 years in ML/AI operations engineering roles. 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 MLflow, SageMaker, Kubeflow or Argo, DVC, Weights and Biases, and other relevant platforms. Strong software engineering abilities in Python/JavaScript/TypeScript Expert in AWS services and containerization technologies like Docker and Kubernetes. Experience with LLMOps frameworks such as LlamaIndex and LangChain. Ability to collaborate effectively with engineering, design, product, and science teams. Strong written and verbal communication skills for reporting and documentation. Proven track record of deploying algorithms and machine learning models into production environments. Demonstrated ability to work closely with multi-functional teams, particularly data scientists. Where can I find out more? Learn more about Evinova www.evinova.com Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/ Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/ Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en Our US Footprint: Powering Scientific Innovation - YouTube Why Evinova? Evinova is a global health tech business, separate company part of the AstraZeneca group. 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 life sciences 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. Join us on our journey of building a new kind of health tech business to reset expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, pioneering cutting-edge methods, and bringing unexpected teams together. Interested? Come and join our journey. Total Rewards: The annual base pay for this position ranges from $ 134,866.40 to $202,299.60. Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an \u201cat-will position\u201d and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. AstraZeneca is an equal opportunity employer that is committed to diversity and inclusion and providing a workplace that is free from discrimination. AstraZeneca is committed to accommodating persons with disabilities. Such accommodation is available on request in respect of all aspects of the recruitment, assessment and selection process and may be requested by emailing AZCHumanResources@astrazeneca.com. 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