Strategic AI/ML Engineer

1 day ago

Ahmedabad, Gujarat, India beBeeArtificialIntelligence Full time US$ 2,00,000 - US$ 2,50,000
Job Description

We are seeking a skilled and motivated AI/ML Engineer with expertise in Large Language Models (LLMs) and multi-agent systems.

The ideal candidate will have a passion for building innovative and intelligent applications that leverage the latest advancements in generative AI.

This is a hands-on role where you will be expected to architect solutions, write high-quality code, and contribute to all phases of the software development lifecycle.

You will work within a fast-paced, collaborative environment, pushing the boundaries of what's possible with AI.

Key Responsibilities:

  • Design & Development: Architect and build complex, multi-agent systems using frameworks like LangGraph and CrewAI.
  • RAG Pipeline Engineering: Develop and optimize advanced RAG architectures, including document processing, vectorization, hybrid search, and contextual reranking to improve the accuracy and relevance of LLM responses.
  • Prompt Engineering & Model Tuning: Expertly craft prompts and utilize various LLM APIs to guide model behavior.
  • Experiment with and integrate open-source models for specific use cases.
  • Infrastructure & Deployment: Implement robust, scalable, and observable production systems.
  • MLOps & Evaluation: Establish and maintain MLOps practices, including rigorous prompt and model evaluation, A/B testing, and telemetry to ensure the reliability and performance of AI systems in production.

Required Skills & Qualifications:

  • Experience: 3+ years of professional experience in software engineering or a related field, with a significant focus on AI/ML.
  • Programming: Advanced proficiency in Python is a must.
  • AI Frameworks: Hands-on experience with LangGraph, CrewAI, LangChain, and LlamaIndex.
  • Agent Systems: Proven track record of designing and building task-oriented AI agents with capabilities such as memory management and inter-agent communication.
  • RAG Architecture: Deep understanding of the full RAG pipeline, including document loaders, chunking strategies, vector embedding models, and contextual reranking algorithms.
  • LLM Tooling: Practical experience with commercial LLMs like OpenAI GPT-4 and integrating and fine-tuning open-source models from platforms like Hugging Face.
  • Infrastructure: Expertise in working with various databases, including Vector DBs and traditional databases.
  • MLOps: Practical experience with prompt engineering, model evaluation metrics, and setting up telemetry and observability for AI applications.

Benefits:

Leadership & Ownership:

Collaboration & Leadership:

As an AI/ML Engineer, you will take full ownership of projects from inception to completion, demonstrating strong ability to work independently, manage timelines, and communicate progress effectively.

Strong written and verbal communication skills are required. Ability to work independently and manage initiatives end-to-end with minimal supervision is essential.

A proactive and curious mindset, with a desire to stay current with the latest developments in the AI field, is highly desirable.

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