Lead AI Engineer

Michael Page; Mumbai; On-site; INR 1,500,000 - 2,500,000; Full time

Benefits offered by this job

Access to state-of-the-art tools

Collaborative work environment

Innovative projects with real-world impact

Job summary

Michael Page is offering an exciting opportunity for a Lead AI Engineer in Mumbai, India. The candidate will drive end-to-end AI projects, leading a team and delivering high-quality solutions using advanced AI technologies. The ideal candidate should have over 5 years of experience in AI/ML engineering, with hands-on experience in building models using frameworks like TensorFlow and PyTorch. This role promises access to innovative tools and a collaborative work environment focused on technical excellence.

Qualifications

• 5+ years of experience in AI/ML engineering focused on production-grade solutions.
• Experience leading teams in AI/ML projects.
• Hands-on expertise in machine learning frameworks.

Responsibilities

• Lead a team of engineers and data scientists on AI projects.
• Design and develop AI models for business challenges.
• Oversee the full lifecycle of AI solutions.

Skills

Building and deploying machine learning models

Programming in Python

Experience with AI/ML projects

Education

Degree in Computer Science, Data Science, or related field

Tools

TensorFlow

PyTorch

AWS

Azure

GCP

Job description

Opportunity Highlights

• Opportunity to drive end‑to‑end AI impact at scale
• Alignment with advanced, applied AI problem‑solving

About Our Client

The company is a AI driven company

Job Description

The key responsibilities include:

• Model Development: Design, develop, and optimize cutting‑edge AI/ML models, including deep learning, reinforcement learning, NLP, and computer vision solutions, to address business and technical challenges.
• Project Leadership: Lead a small team of 2–5 engineers and data scientists on 2–3 AI projects simultaneously, ensuring timely delivery, high‑quality outcomes, and alignment with organizational goals.
• End‑to‑End Implementation: Oversee the full lifecycle of AI solutions, from data pre‑processing and feature engineering to model training, evaluation, deployment and monitoring in production environments.
• Collaboration: Work closely with cross‑functional teams, including product managers, software engineers, and domain experts, to integrate AI solutions into scalable, production‑ready systems.
• Innovation: Stay abreast of the latest advancements in AI/ML research and technologies, and propose innovative approaches to enhance existing systems and workflows.
• Mentorship: Guide and mentor junior engineers and team members, fostering a culture of technical excellence and continuous learning.
• Performance Optimization: Optimize AI models for performance, scalability, and efficiency, ensuring they meet latency, throughput, and resource constraints in production.
• Code Quality: Write clean, maintainable, and well‑documented code, adhering to best practices and contributing to shared codebases.

The Successful Applicant

A successful Lead AI Engineer should have:

• A strong educational background in Computer Science, Data Science, or a related field.
• 5 + years of professional experience in AI/ML engineering, with a focus on developing and deploying production‑grade AI solutions.
• Proven experience leading small teams (2–5 members) on 2–3 AI/ML projects, delivering successful outcomes from ideation to production.
• Hands‑on expertise in building and deploying machine learning models using frameworks such as TensorFlow, PyTorch, Scikit‑learn, or similar.
• Strong programming skills in Python, with experience in production‑level coding and software engineering practices.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and deploying AI models in distributed, scalable environments.
• Deep understanding of machine learning algorithms, neural networks, and statistical modelling.
• Proficiency in working with large datasets and tools such as Pandas, NumPy, or SQL.
• Experience with model optimization techniques, such as quantization, pruning, and distributed training.
• Knowledge of MLOps practices, including model versioning, CI/CD pipelines, and monitoring in production.

What’s on Offer

• Opportunity to work on cutting‑edge AI projects with real‑world impact.
• Collaborative and innovative work environment with a focus on technical excellence.
• Access to state‑of‑the‑art tools, technologies, and resources to fuel your success.