AstraZeneca-posted 3 months ago
$134,866 - $202,299/Yr
Full-time • Senior
Gaithersburg, MD
5,001-10,000 employees

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.

  • 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.
  • 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.
  • 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.
  • 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.
  • 401(k) plan
  • Paid vacation and holidays
  • Paid leaves
  • Health benefits including medical, prescription drug, dental, and vision coverage
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