Senior Aiml Developer

ManekTech; Gujarat; On-site; INR 576,000 - 960,000; Full time

Job summary

ManekTech in India is seeking a Senior AI/ML Engineer to architect and deploy production-grade AI/ML systems across NLP and computer vision domains. You will own the end-to-end ML lifecycle, develop LLM-powered apps with RAG, and deliver scalable ML/LLM microservices with strong MLOps practices.

Projects will involve vector databases and real-time inference, collaborating with data engineering to build robust data pipelines and production-grade AI platforms.

Qualifications

• Experience with end-to-end ML lifecycle and MLOps.
• Strong knowledge of LLM/RAG pipelines.
• Hands-on in building scalable ML/LLM microservices.
• Experience with vector databases and real-time inference.

Responsibilities

• Design and implement end-to-end ML pipelines (data ingestion → training → deployment → monitoring).
• Build LLM-powered applications using RAG and agentic workflows.
• Develop scalable ML/LLM microservices (FastAPI or similar).
• Implement MLOps/LLMOps best practices and CI/CD for ML.
• Optimize latency, throughput and cost of AI systems.
• Collaborate with data engineering for robust data pipelines.
• Lead AI system architecture decisions and mentor juniors.

Skills

Python development

End-to-end ML lifecycle

LLM/RAG pipelines

Microservices

Tools

FastAPI

Docker

Kubernetes

AWS SageMaker

GCP Vertex AI

Job description

Senior AI/ML Developer

About the Role

We are looking for a Senior AI/ML Engineer to architect and deploy production-grade AI/ML and Generative AI systems across domains such as NLP, Computer Vision, and deep learning.

This role requires strong expertise in the end-to-end ML lifecycle, LLM/RAG pipelines, scalable backend systems, and MLOps/LLMOps.

You will build scalable, reliable, and cost-efficient AI platforms used in real-world applications.

Key Responsibilities

• Design and implement end-to-end ML pipelines
• (data ingestion → preprocessing → training → deployment → monitoring)
• Build LLM-powered applications using RAG and agentic workflows
• Develop scalable ML/LLM microservices (FastAPI or similar)
• Implement MLOps/LLMOps best practices
• Optimize latency, throughput, and cost of AI systems
• Work with vector databases for semantic search and retrieval
• Design batch and real-time inference systems
• Collaborate with data engineering for robust data pipelines
• Lead AI system architecture decisions
• Mentor junior engineers and enforce production-quality standards

Tech Stack

Programming & Core

• Python (production-grade)
• JavaScript, React JS(Bonus)
• Strong SQL

AI/ML & Deep Learning

• PyTorch / TensorFlow
• Scikit-learn
• Hugging Face ecosystem
• Model evaluation & optimization tools
• Applied Mathametics for Machine Learning

Generative AI / LLM

• Gen AI Orchestration frameworks (LangChain , Langgraph , LlamaIndex , CrewAI Autogen or equivalent)
• Embeddings pipelines
• LLM evaluation frameworks
• Prompt orchestration systems
• Agentic workflow frameworks (preferred)
• Vector Databases

MLOps / LLMOps

• MLflow , Langsmith etc.
• Model registry & versioning
• CI/CD for ML (GitHub Actions, GitLab CI, etc.)
• Data validation (Great Expectations or similar)
• Model monitoring & observability
• Opentelemetry, Grafana

Backend & Systems

• FastAPI / Flask / Django
• Async Python
• Microservices architecture
• REST/gRPC APIs
• Docker
• Kubernetes
• Message queues (Kafka / RabbitMQ – bonus)

Cloud & Infrastructure (at least one)

• AWS (SageMaker, ECR, ECS/EKS, Lambda, S3)
• GCP (Vertex AI, GKE, Cloud Run, BigQuery)
• Azure ML (preferred)
• GPU-based deployment and optimization

Pay: Up to ₹960,000.00 per year

Ability to commute/relocate:

• Ahmedabad, Gujarat: Reliably commute or planning to relocate before starting work (Preferred)

Experience:

• AIML: 1 year (Preferred)

Work Location: In person