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.
