Lead AI Engineer

Lead AI Engineer

• Experience: 5+ years (entirely in AI/ML domain)

• Engagement type: Full-time / Freelancer / Contractor / Consultant Engineer

• Preferred work location: Magarpatta City, Pune office (for all engagement types)

Role Summary

We are hiring a Lead AI Engineer who is a true generalist across the AI ecosystem and can lead, mentor, and scale a team of AI/ML engineers. This opportunity is open across full-time, freelancer, contractor, and consultant engineer engagement types. You will architect AI solutions, code hands-on, guide teams across varied AI initiatives, and deliver end-to-end AI projects spanning classical ML, deep learning, SLMs/LLMs, multimodal systems, MLOps, optimization, and production deployment. For all engagement types, preference is for working from our Magarpatta City, Pune office.

Key Responsibilities

Technical Leadership

· Lead end-to-end AI solution development across multiple workstreams.

· Convert problem statements into clear architectures and execution plans.

· Guide design, training, evaluation, optimization, and deployment of models.

· Ensure code quality, engineering excellence, and scalable ML system design.

Hands-On Engineering

· Contribute to coding, experimentation, fine-tuning, and optimization.

· Build quick prototypes and convert them into production pipelines.

· Create reusable components, tools, and frameworks.

Team Leadership

· Manage and mentor AI/ML/Data engineers.

· Drive sprint planning, estimation, and code reviews.

· Build a culture of high output, learning, and experimentation.

Project & Delivery

· Own technical delivery across concurrent AI initiatives.

· Work with product, data, engineering, and business teams.

· Manage risks and ensure predictable delivery.

AI Strategy

· Stay current with emerging AI research, LLMs, multimodal systems, and agentic workflows.

· Integrate state-of-the-art models where relevant.

· Improve ML lifecycle efficiency via automation and tooling.

MLOps & Production

· Oversee scalable training, deployment, lifecycle management, and monitoring.

· Ensure reproducibility, reliability, and CI/CD best practices.

Required Skills & Qualifications

Core Technical Expertise

· 5+ years in deep learning, LLMs, CV, NLP, RL, applied ML, and MLOps.

· Strong Python and ML frameworks (PyTorch, TensorFlow, JAX).

· Experience with LLM fine-tuning, prompt engineering, adapters, RAG, vector DBs, multimodal pipelines.

· Strong classical ML grounding.

· Experience with distributed training and GPU/accelerator optimization.

Architecture & System Design

· End-to-end AI system architecture (training → inference → monitoring).

· Knowledge of microservices, APIs, cloud (AWS/Azure/GCP), containers.

MLOps

· Experience with experiment tracking, feature stores, model registry, CI/CD for ML, monitoring, and retraining.

Education

· Bachelor’s/Master’s in Computer Science, AI, ML, Data Science, or related fields.

What You’ll Drive

· Development of cutting-edge AI capabilities.

· Scaling and shaping the AI engineering function.

· High-impact technical leadership and hands-on contribution.

• 5+ years in deep learning, LLMs, CV, NLP, RL, applied ML, and MLOps
• Strong Python and ML frameworks (PyTorch, TensorFlow, JAX)
• Experience with LLM fine-tuning, prompt engineering, adapters, RAG, vector DBs, multimodal pipelines
• Strong classical ML grounding
• Experience with distributed training and GPU/accelerator optimization
• End-to-end AI system architecture (training → inference → monitoring)
• Knowledge of microservices, APIs, cloud (AWS/Azure/GCP), containers
• Experience with experiment tracking, feature stores, model registry, CI/CD for ML, monitoring, and retraining
• Bachelor's/Master's in Computer Science, AI, ML, Data Science, or related fields