AI/ML Engineer

Primary Responsibilities

Design, develop, and deploy production-ready AI/ML solutions for enterprise applications.

Build and optimize Large Language Model (LLM) applications, AI agents, and Retrieval-Augmented Generation (RAG) pipelines.

Fine-tune, evaluate, and optimize open-source and commercial AI models for specific business use cases.

Develop scalable APIs and AI services using Python frameworks such as FastAPI or Flask.

Build intelligent automation workflows using AI, vector databases, and orchestration frameworks.

Design and implement machine learning pipelines for data preprocessing, feature engineering, model training, validation, and deployment.

Collaborate with Product Managers, Architects, UI/UX Designers, and DevOps teams to deliver AI-powered products.

Optimize model inference performance, latency, and infrastructure costs.

Mentor junior AI engineers and participate in architecture discussions, technical reviews, and code reviews.

Research and evaluate emerging AI technologies and recommend adoption where appropriate.

Ensure AI applications follow security, privacy, and responsible AI best practices.

Technical RequirementsProgramming Languages

Strong expertise in Python.

Good knowledge of SQL.

Basic understanding of JavaScript or TypeScript for AI integrations.

Artificial Intelligence & Machine Learning

Strong experience with Machine Learning, Deep Learning, NLP, and Generative AI.

Hands-on experience with LLMs such as GPT, Claude, Llama, Qwen, Mistral, or Gemma.

Experience developing AI Agents and multi-agent workflows.

Strong understanding of prompt engineering, structured outputs, function calling, and tool integration.

Experience implementing Retrieval-Augmented Generation (RAG) architectures.

Knowledge of embedding models and semantic search.

AI Frameworks (Any)

LangChain

LangGraph

LlamaIndex

Haystack (preferred)

OpenAI SDK

Hugging Face Transformers

Sentence Transformers

Machine Learning Frameworks (Any)

PyTorch

TensorFlow

Scikit-learn

XGBoost

LightGBM

Vector Databases (Any)

Pinecone

Qdrant

Milvus

ChromaDB

FAISS

Backend Development

FastAPI

Flask

RESTful APIs

WebSockets

Background workers (Celery/RQ)

Databases (Any)

PostgreSQL

MongoDB

Redis

Cloud & Infrastructure (Any)

AWS, Azure, or Google Cloud Platform

Docker

Kubernetes (preferred)

Git

CI/CD pipelines

Linux environments

MLOps (Any)

MLflow

Weights & Biases

Model versioning

Model deployment

Monitoring and observability

GPU optimization and inference serving

Computer Vision (Preferred) (Any)

OpenCV

YOLO

OCR

Image classification

Object detection

Pose estimation

Voice AI (Preferred)

Speech-to-Text (STT)

Text-to-Speech (TTS)

Real-time voice assistants

Voice activity detection

Audio streaming

Additional Skills

Strong knowledge of software architecture and design patterns.

Experience building scalable AI SaaS platforms.

Understanding of API security, authentication, and data privacy.

Excellent debugging and performance optimization skills.

Familiarity with Agile/Scrum development methodology.

Experience

Minimum Years of Experience: 5+ Years

Relevant Industry Experience: Minimum 5 years of hands-on experience in Artificial Intelligence, Machine Learning, and Deep Learning, including 2+ years of experience building production-ready Generative AI and LLM-based applications.

Apply : ayushi@moontechnolabs.com

Work Location: In person