SENIOR MANAGER - MACHINE LEARNING ENGINEER (GENAI LEAD)

Summary The APAC Business Technology Team within Johnson & Johnson Innovative Medicine, is looking for an extraordinary GenAI and Machine Learning Engineering Lead who is passionate about crafting, developing, and fielding data science solutions that drive impact for HCP (Health Care Professional) and patients.
As the regional Gen AI and Machine Learning engineer, you will be responsible for designing and building GenAI and machine learning engineering solutions across the region.
You will leverage your technical expertise, experience, and communication skills to work across business & technology teams productionize innovative data science models and applications.
Your technical knowledge and ability to apply them, will be paramount to your success in this role.
Focus areas include (but not limited) to patient analytics, commercial strategy, and patient support program analytics.
Specifically, you will build end-to-end machine learning pipelines by developing and applying creative solutions that go beyond current tools and work together with data scientist to deliver scalable, reusable, extensible and flexible solution.
Deliver end to end GenAI and machine learning applications for our key projects across the region.
Execute the regional GenAI strategy including people, technology, platforms, and process.
Collaborate with platform teams and solution architect to evolve our big data platforms and evaluate various data science technologies and services.
Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.
You will be someone who stays on the cutting edge of artificial intelligence, data science and software engineering through novel project execution and development of algorithms that improve organizational performance and commercial effectiveness.
The role requires both a broad knowledge of existing software development lifecycle, AI algorithms and the creativity to invent and customize when necessary.
You will work with matrixed teams across business and technology, and will be part of a dynamic, accomplished organization that will support multiple therapeutic areas.
Responsibilities GenAI Solution Architecture Design and Implementation Lead a team of AI engineers, and DevOps specialists to design, develop, and optimize Generative AI architectures tailored to specific use cases and business requirements.
Collaborate with data scientist to drive the end-to-end implementation of GenAI models, including training, fine-tuning, and deployment.
Prompt Engineering Collaborate with data scientists to create and refine prompts for various AI applications Develop advanced prompt engineering techniques to enhance the performance and accuracy of GenAI models.
Machine Learning Solution build and deployment.
Collaborate with data scientist and other technology teams to design and build machine learning engineering solution for the region.
Establish and maintain ML pipelines to automate the training, testing, and deployment of AI models.
Implement CI/CD practices to ensure continuous integration and delivery of AI solutions.
Monitor and manage the lifecycle of deployed models, ensuring they meet performance and reliability standards.
Cloud AI Solutions (AWS and Azure).
Architect and implement scalable AI solutions on cloud platforms such as AWS and Azure.
Utilize cloud services to manage and deploy AI models, ensuring high availability and performance.
Research and Innovation.
Stay updated with the latest advancements in Generative AI, cloud technologies, and MLOps practices, and bring them to the team.
Drive innovation by exploring new tools, techniques, and methodologies to improve AI capabilities and efficiencies.
Qualifications Required Minimum Education.
Bachelor’s degree Required Years of Related Experience.
Minimum of 7 years professional experience is required with a minimum of 5 years building machine learning model development is preferred Proven track record in designing and building GenAI solutions, with a strong expertise in prompt engineering, LlamaIndex, Langchain, RAG, AI red teaming libraries, LLM monitoring and evaluation.
Minimum 4+ years of experience in Machine learning engineering and MLOps, developing end-to-end machine learning pipelines.
Must have a proven ability to take solutions to production, while effectively monitoring and maintaining them.
Over 7+ years of experience in the software development lifecycle as a developer, with a focus on writing production code.
Must have hands-on experience working with software development toolkits, and devOps automation like Kubernetes, Airflow, Jenkins, Jira, Confluence and Git.
Excellent programming skills in Python and proficiency in PySpark.
Experience in DataBricks, AWS Sagemaker and Azure ML is plus.
Strong leadership skill with ability to influence the thought process and drive alignment.
Excellent communication skills and a demonstrated ability to collaborate effectively with cross-functional teams.
Self-motivated and highly driven individual who can thrive in ambiguous requirements.