AI Tech Lead - Machine Learning/Deep Learning

About DevsTree IT Services Pvt Ltd

Position Overview

Key Responsibilities

• Architect, design, and build AI-driven solutions and intelligent workflows using ML, DL, and Gen AI tools.
• Lead the end-to-end development of Machine Learning/Deep Learning models from data gathering and feature engineering to model deployment and monitoring.
• Build and fine-tune Large Language Models (LLMs) and integrate them with external business systems via APIs.
• Develop solutions leveraging Computer Vision, including object detection, image classification, OCR, face recognition, etc.
• Implement and scale NLP models for tasks such as document understanding, semantic search, summarization, chatbots, and conversational AI.
• Develop and orchestrate Agentic workflows using autonomous agents and low-code tools like n8n for automating multi-step business actions.
• Stay updated on the latest trends in Gen AI, multimodal models, and tools such as Lang Chain, Llama Index, Haystack, etc.
• Use ML flow for experiment tracking, model versioning, and reproducible machine learning pipelines.
• Collaborate with cross-functional teams including Product Managers, Data Engineers, and UI/UX Designers to define scalable AI-driven features.
• Conduct technical reviews, ensure code quality, and mentor junior AI engineers.
  

Required Skills & Qualifications

• 67 years of experience in AI/ML, including at least 3+ years in a tech lead or senior engineering role.
• Strong proficiency in Python and ML/DL libraries : TensorFlow, PyTorch, scikit-learn, OpenCV, Hugging Face, SpaCy, etc.
• Hands-on experience in building and deploying models in Computer Vision and NLP domains.
• Deep understanding of LLMs (e.g., GPT, LLa MA, Mistral, Claude) and prompt engineering.
• Experience with Lang Chain, Llama Index, Open AI API, Anthropic, or custom model fine-tuning.
• Experience working with n8n for automating data pipelines, AI agent orchestration, or external integrations.
• Experience building autonomous agents or integrating with agentic frameworks like Auto GPT, Baby AGI, or Crew AI is a strong plus.
• Hands-on with MLflow for experiment tracking and model lifecycle management.
• Familiarity with cloud platforms (AWS/GCP/Azure), containerization (Docker), and model deployment tools (Fast API, Flask, Streamlit, etc.
• Strong communication and interpersonal skills, with the ability to explain complex AI solutions to technical and non-technical stakeholders.
  

Preferred Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Exposure to tools like Kubeflow, Airflow, or Vertex AI is a plus.
• Experience in building AI-powered mobile or web applications.
• Understanding of data privacy, model ethics, and explainability in AI systems.