AI/ML Systems Engineer

2 days ago

Anand, Gujarat, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

About Us

We are a cutting-edge technology company that helps businesses grow their revenues via WhatsApp.

  • Enabling 100,000+ businesses with WhatsApp engagement and marketing.
  • 400 Crores+ WhatsApp messages exchanged between businesses and users per year.
  • Working with top brands like Delhi Transport Corporation, Vivo, Physicswallah, and more.
  • High impact as businesses drive 25-80% revenues using our platform.
Job Overview

We are looking for a senior machine learning engineer to lead the development and deployment of AI/ML systems with a strong focus on large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and intelligent automation.

You will work closely with cross-functional teams to translate business needs into AI solutions, bringing your expertise in building scalable ML infrastructure, deploying models in production, and staying at the forefront of AI innovation.

Key Responsibilities

Ai System Development

  • Design, develop, and optimize end-to-end ML models using LLMs, transformer architectures, and custom RAG frameworks.
  • Fine-tune and evaluate generative and NLP models for business-specific applications such as conversational flows, auto-replies, and intelligent routing.
  • Lead prompt engineering and build autonomous AI agents capable of executing multi-step reasoning.

Infrastructure, Deployment & MLOps

  • Architect and automate scalable training, validation, and deployment pipelines using tools like MLflow, SageMaker, or Vertex AI.
  • Integrate ML models with APIs, databases (vector/graph), and production services ensuring performance, reliability, and traceability.
  • Monitor model performance in real-time, and implement A/B testing, drift detection, and re-training pipelines.

Data & Feature Engineering

  • Work with structured, unstructured, and semi-structured data (text, embeddings, chat history).
  • Build and manage vector databases (e.g., Pinecone, Weaviate) and graph-based retrieval systems.
  • Ensure high-quality data ingestion, feature pipelines, and scalable pre-processing workflows.

Team Collaboration & Technical Leadership

  • Collaborate with product managers, software engineers, and stakeholders to align AI roadmaps with product goals.
  • Mentor junior engineers and establish best practices in experimentation, reproducibility, and deployment.
  • Stay updated on the latest in AI/ML (LLMs, diffusion models, multi-modal learning), and drive innovation in applied use cases.

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