Associate Director - AI/ML Engineering

Associate Director - AI/ML Engineering

What you will do

We are seeking a Associate Director of ML / AI Engineering to lead Amgen Indias AI engineering practice. This role is integral to developing top-tier talent, setting ML / AI best practices, and evangelizing ML / AI Engineering capabilities across the organization. The Associate Director will be responsible for driving the successful delivery of strategic business initiatives by overseeing the technical architecture, managing talent, and establishing a culture of excellence in ML / AI

The key aspects of this role involve :

(1) prior hands-on experience building ML and AI solutions

(2) management experience in leading ML / AI engineering team and talent development

(3) Delivering AI initiatives at enterprise scale

Roles & Responsibilities:

• Talent Growth & People Leadership: Lead, mentor, and manage a high-performing team of engineers, fostering an environment that encourages learning, collaboration, and innovation. Focus on nurturing future leaders and providing growth opportunities through coaching, training, and mentorship.
• Recruitment & Team Expansion: Develop a comprehensive talent strategy that includes recruitment, retention, onboarding, and career development and build a diverse and inclusive team that drives innovation, aligns with Amgen's culture and values, and delivers business priorities
• Organizational Leadership: Work closely with senior leaders within the function and across the Amgen India site to align engineering goals with broader organizational objectives and demonstrate leadership by contributing to strategic discussions
• Create and implement a strategy for expanding the AI/ML engineering team, including recruitment, onboarding, and talent development.
• Oversee the end-to-end lifecycle of AI/ML projects, from concept and design through to deployment and optimization, ensuring timely and successful delivery.
• Ensure adoption of ML-Ops best practices, including model versioning, testing, deployment, and monitoring.
• Collaborate with multi-functional teams, including product, data science, and software engineering, to find opportunities and deliver AI/ML solutions that drive business value.
• Serve as an AI/ML evangelist across the organization, promoting awareness and understanding of the capabilities and value of AI/ML technologies.
• Promote a culture of innovation and continuous learning within the team, encouraging the exploration of new tools, technologies, and methodologies.
• Provide technical leadership and mentorship, guiding engineers in implementing scalable and robust AI/ML systems.
• Work closely with collaborators to prioritize AI/ML projects and ensure timely delivery of key initiatives.
• Lead innovation initiatives to explore new AI/ML technologies, platforms, and tools that can drive further advancements in the organizations AI capabilities.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients.

Basic Qualifications:

• Masters degree and 12 to 14 years of computer science, Artificial Intelligence, Machine Learning experience OR
• Bachelors degree and 14 to 18 years of computer science, Artificial Intelligence, Machine Learning experience OR
• Diploma and 18 to 20 years of computer science, Artificial Intelligence, Machine Learning experience

Preferred Qualifications:

• Experience in building AI Platforms & applications at enterprise scale
• Expertise in AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Hands-on experience with LLMs, Generative AI, and NLP (e.g., GPT, BERT, Llama, Claude, Mistral AI)
• Strong understanding of MLOps processes and tools such as MLflow, Kubeflow, or similar platforms.
• Proficient in programming languages such as Python, R, or Scala.
• Experience deploying AI/ML models in cloud environments (AWS, Azure, or Google Cloud).
• Proven track record of managing and delivering AI/ML projects at scale.
• Excellent project management skills, with the ability to lead multi-functional teams and manage multiple priorities.
• Experience in regulated industries, preferably life sciences and pharma

Good-to-Have Skills:

• Experience with natural language processing, computer vision, or reinforcement learning.
• Knowledge of data governance, privacy regulations, and ethical AI considerations.
• Experience with cloud-native AI/ML services (Databricks, AWS, Azure ML, Google AI Platforms)
• Experience with AI Observability

Professional Certifications (Preferred):

• Google Professional Machine Learning Engineer, AWS Certified Machine Learning, or Azure AI Engineer Associate, Databricks Certified Generative AI Engineer Associate

Soft Skills:

• Excellent leadership and communication skills, with the ability to convey complex technical concepts to non-technical collaborators.
• Ability to foster a collaborative and innovative work environment.
• Strong problem-solving abilities and attention to detail.
• High degree of initiative and self-motivation.
• Ability to mentor and develop team members, promoting their growth and success.