Associate Director

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.

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.