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AI/ML Lead Engineer

Roles & Responsibilities

  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning or related field
  • 14+ years of IT experience with a minimum of 6+ years in AI/ML
  • Experience in AI/ML engineering, particularly with building LLM-based applications and prompt-driven architectures
  • Solid understanding of Retrieval-Augmented Generation (RAG) patterns and vector databases (especially Qdrant)

Requirements:

  • Design and develop production-grade AI/ML models for real-world applications (e.g., recommendation engines, NLP, computer vision, forecasting)
  • Lead model lifecycle management from experimentation and prototyping to deployment and monitoring
  • Collaborate with cross-functional teams to define AI-driven features and services and drive data-driven decision making
  • Build and maintain scalable AI infrastructure using cloud services (AWS, Azure, GCP) and MLOps best practices; mentor junior AI/ML engineers

Job description


Role: AI/ML Lead Engineer
Position Type: Full-Time Contract (40hrs/week)
Contract Duration: 6 Months
Work Schedule: 8 hours/day (Mon-Fri)
Location: 100% Remote (Candidates can work from anywhere in India)

We are seeking a highly skilled and experienced AI/ML Engineer to lead the design, development, and deployment of advanced AI solutions across our enterprise. The ideal candidate will have a deep understanding of AI/ML algorithms, scalable systems, and data engineering best practices.

Key Responsibilities:

Design and develop production-grade AI and machine learning models for real-world applications (e.g., recommendation engines, NLP, computer vision, forecasting).
• Lead model lifecycle management from experimentation and prototyping to deployment and monitoring.
• Collaborate with cross-functional teams (product, data engineering, MLOps, and business) to define AI-driven features and services.
• Perform feature engineering, data wrangling, and exploratory data analysis on large-scale structured and unstructured datasets.
• Build and maintain scalable AI infrastructure using cloud services (AWS, Azure, GCP) and MLOps best practices.
• Mentor junior AI/ML engineers, guiding them in model development, evaluation, and deployment.
• Continuously improve model performance by leveraging new research, retraining on new data, and optimizing pipelines.
• Stay current with the latest developments in AI, machine learning, and deep learning through research, conferences, and publications.

Required Skills and Qualifications:

  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning or related field.
  • 14+ years of IT experience with a minimum of 6+ years of AI/ML
  • Experience in AI/ML engineering, particularly with building LLM-based applications and prompt-driven architectures.
  • Solid understanding of Retrieval-Augmented Generation (RAG) patterns and vector databases (especially Qdrant).
  • Hands-on experience in deploying and managing containerized services in AWS ECS and using CloudWatch for logs and diagnostics.
  • Familiarity with AWS Bedrock and working with foundation models through its managed services.
  • Experience working with AWS RDS (MySQL or MariaDB) for structured data storage and integration with AI workflows.
  • Practical experience with LLM fine-tuning techniques, including full fine-tuning, instruction tuning, and parameter-efficient methods like LoRA or QLoRA.
  • Strong understanding of recent AI advancements such as multi-agent systems, AI assistants, and orchestration frameworks.
  • Proficiency in Python and experience working directly with LLM APIs (e.g., OpenAI, Anthropic, or similar).
  • Comfortable working in a React frontend environment and integrating backend APIs.
  • Experience with CI/CD pipelines and infrastructure as code (e.g., Terraform, AWS CDK).

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