We are seeking a highly skilled Team Lead to lead end-to-end advanced AI/ML initiatives across the organization. This role goes beyond technical executionrequiring strategic thinking, solution architecture, cross-functional leadership, and direct engagement with clients and business stakeholders. The Principal ML Engineer will provide technical leadership, drive innovation, mentor engineering teams, and ensure scalable and high-impact delivery of machine learning solutions.

Key Responsibilities :

Technical Leadership & Architecture :

- Lead the design and architecture of scalable machine learning systems, pipelines, and infrastructure across multiple product lines.

- Evaluate and select appropriate ML frameworks, tools, and platforms based on business and technical requirements.

- Drive innovation in MLOps, automation, monitoring, and optimization to deliver reliable and continuously improving ML systems.

- Perform high-level code reviews, enforce best practices, and provide guidance on patterns and frameworks.

- Oversee model lifecycle from research, experimentation, training, and validation to deployment and monitoring.

Project & Delivery Ownership :

- Own ML solution roadmaps and coordinate delivery across engineering, data science, product, and DevOps teams.

- Define and review project milestones, success metrics, and performance guidelines.

- Ensure ML models meet security, scalability, compliance, and governance standards.

- Identify risks proactively and drive mitigation strategies to ensure smooth execution and delivery.

Team Leadership & People Management :

- Manage, mentor, and upskill ML engineers, data scientists, and cross-functional teams.

- Support hiring, onboarding, and capability building for the growing ML team.

- Facilitate technical workshops, knowledge-sharing sessions, and performance reviews.

- Foster a collaborative, inclusive, and innovation-driven engineering culture.

Client & Stakeholder Management :

- Collaborate with clients, business leaders, and product owners to translate business requirements into actionable ML solutions.

- Communicate ML project plans, results, challenges, and recommendations to both technical and non technical audiences.

- Represent the ML practice in executive-level discussions, solution presentations, and customer engagements.

Research & Thought Leadership :

- Stay current with emerging AI/ML trends, frameworks, and research advancements.

- Evaluate and implement modern models including foundation models, generative AI, NLP, CV, and reinforcement learning where applicable.

- Promote reusable ML components, patterns, frameworks, and engineering excellence across the organization.

Required Skills and Experience :

- 10 to 12+ years of experience in AI/ML engineering, with at least 4+ years in a technical leadership or architectural role.

- Strong expertise in machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, etc.

- Proven experience deploying ML models in production using MLOps frameworks (Kubeflow, MLflow, Airflow, Vertex AI, SageMaker, or equivalent).

- Strong programming expertise in Python and proficiency with distributed computing frameworks (Spark, Ray, Databricks, etc.).

- Experience with cloud AI environments (AWS, GCP, Azure).

- Excellent communication, stakeholder handling, and leadership skills.