Team Lead - AI/ML

We are seeking a highly skilled Senior Team Lead to lead end-to-end advanced AI/ML initiatives across the organization. This role goes beyond technical execution—requiring 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

8–12+ years of experience in AI/ML engineering, with at least 2+ 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.