Manager, ML Engineering

About the role

Based in Hyderabad, join a global healthcare biopharma company and be part of a 130- year legacy of success backed by ethical integrity, forward momentum, and an inspiring mission to achieve new milestones in global healthcare. Be part of an organisation driven by digital technology and data-backed approaches that support a diversified portfolio of prescription medicines, vaccines, and animal health products. Drive innovation and execution excellence. Be a part of a team with passion for using data, analytics, and insights to drive decision-making, and which creates custom software, allowing us to tackle some of the world's greatest health threats. Our Technology Centers focus on creating a space where teams can come together to deliver business solutions that save and improve lives. An integral part of our company's IT operating model, Tech Centers are globally distributed locations where each IT division has employees to enable our digital transformation journey and drive business outcomes. These locations, in addition to the other sites, are essential to supporting our business and strategy. A focused group of leaders in each Tech Center helps to ensure we can manage and improve each location, from investing in growth, success, and well-being of our people, to making sure colleagues from each IT division feel a sense of belonging to managing critical emergencies. And together, we must leverage the strength of our team to collaborate globally to optimize connections and share best practices across the Tech Centers. Role Overview As an AI Engineering manager you will help build, manage and develop a team of 3-4 AI, cloud and full stack engineers. You will collaborate with your AI engineering colleagues, AI manager and Tech Lead in other Technology centers. You will overlook design and building of AI solutions operated on cloud-based platforms that address complex business problems. You will apply your expertise in programming (such as Python), modern software engineering, MLOps practices, machine learning, large language models (LLMs), retrieval-augmented generation (RAG), to make sure team delivers robust AI solutions that meet business, organizational and end-user needs. You will work closely with product managers, product owners, AI tech lead, data scientists, architects, and engineers across global teams to design systems, determine functional and non-functional needs and implement solutions accordingly. You should be ready to work independently as well as in a team. What will you do in this role Collaborate with global stakeholders and partners to evaluate value of AI engineering projects. Act as people manager and mentor to junior and mid-level engineers, driving best practices in platform engineering, software development, infrastructure management, and DevOps methodologies. Overlook team writing efficient, maintainable, and secure code following software engineering best practices. Design and deliver backend, front end services and AI platform components with high scalability and reliability. Architect, deploy, and operate cloud-native infrastructure (primarily AWS or GCP). Apply Infrastructure-as-Code, containerization and Kubernetes at scale Create and review usage of DevOps best practices, maintaining CI/CD pipelines (GitHub Actions, Argo CD) for automated build, test, deployment, and monitoring. What should you have Bachelors' degree in Information Technology, Computer Science or any Technology stream. 7-11 years of hands-on experience in software engineering, including 3 years in AI engineering, including 3 years of people management experience. Primary skills (must-have) Past international job experience. Ability to communicate and collaborate in diverse multi-cultural environment. Strong communication and collaboration skills, with the ability to manage multiple priorities through analytical, detail-oriented and customer-focused approaches. Strong hands-on Python skills; ability to review code and mentor engineers. Proven experience building scalable AI solutions within a modern technology stack (cloud services, data pipelines, databases, etc). Solid understanding of machine learning and GenAI concepts. Demonstrated experience designing and deploying cloud-native solutions on AWS exposure to GCP is a plus. Experience with DevOps practices (Git, Docker, infrastructure as code, observability, continuous integration/continuous deployment - CI/CD). Secondary skills (nice to have) Experience working in Agile methodology. Experience with AWS Cloud, ideally A

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Job Description Required Skills: Amazon Web Services (AWS), Docker (Software), Git, LangChain (FrameWork), Python (Programming Language), Structured Query Language (SQL), Terraform (Software) Preferred Skills: AI Ops, Google Cloud Platform (GCP), JavaScript, Machine Learning (ML), TypeScript Current Employees apply HERE Current Contingent Workers apply HERE Secondary Language(s) Job Description: Manager- ML Engineer

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