Machine Learning Engineer

Propelis Group; India; À distance; INR 1 800 000 - 2 400 000; Plein temps

Résumé du poste

Propelis Group is seeking an experienced Senior AI/ML Developer to lead machine learning engineering initiatives, designing scalable, production-ready AI solutions. You will bridge technical architecture, hands-on development, and team leadership to drive end-to-end ML lifecycles from prototyping to cloud deployment.

You will architect ML pipelines, adopt LLMs and OCR/document intelligence, manage AWS SageMaker-based infrastructure, containerized services with Docker, and mentor the team to

Qualifications

• 5+ years of progressive software engineering and AI/ML experience with architecture leadership.
• Hands-on experience deploying ML models to production in cloud environments.
• Strong communication and team leadership with cross-functional collaboration.

Responsabilités

• Lead end-to-end ML pipelines and microservices for production workloads.
• Design scalable AWS cloud infrastructure and containerized deployments.
• Mentor engineers, conduct code reviews, and align AI roadmaps with business goals.
• Evaluate models, optimize latency, and ensure cost governance.

Connaissances

AI/ML leadership

Python

Cloud deployment

Outils

Hugging Face

PyTorch

FastAPI

Docker

Description du poste

Position Overview

We are seeking an experienced and vision-driven Senior AI/ML Developer to lead our machine learning engineering initiatives and design scalable, production-ready AI solutions. In this role, you will bridge technical architecture, hands‑on development, and team leadership driving end‑to‑end Machine Learning lifecycles from rapid prototyping and fine‑tuning to containerized cloud deployment and monitoring.

Key Responsibilities

Technical Leadership & Architecture

• Architect, design, and implement end‑to‑end Machine Learning pipelines and microservices for production workloads.
• Lead the adoption of state‑of‑the‑art Large Language Models (LLMs), Vision‑Language Models (VLMs), and OCR/Document Intelligence frameworks (e.g., Qwen VL, Gemma variants, PyMuPDF, Docling, OpenCV).
• Standardize core engineering workflows including model quantization, LoRA/PEFT fine‑tuning, and multi‑adapter serving architectures using vLLM, llama.cpp, and Hugging Face Transformers.

Cloud Infrastructure & MLOps

• Design and manage scalable AWS cloud infrastructure leveraging SageMaker, Lambda, ECS Fargate, S3, ECR, and SQS.
• Containerize microservices using Docker and Docker Compose, establishing robust CI/CD pipelines (GitLab CI/CD, Git) for automated testing and deployment.
• Serve high‑performance inference APIs using frameworks like FastAPI and optimized backend engines.

Team Management & Delivery

• Lead and mentor an engineering team , conducting code reviews, technical planning, and sprint delivery.
• Partner with cross‑functional stakeholders, product managers, and executive leadership to translate business objectives into high‑impact AI capability roadmaps.
• Define technical standards, design patterns, and best practices across model evaluation, security, latency optimization, and cost governance.

Key Qualifications

• Experience: 5+ years of progressive software engineering and AI/ML experience, with demonstrated hands‑on leadership as an Architect.

Core Technical Stack

• Languages: Python (PyTorch, FastAPI, NumPy, Pandas, PIL)
• Frameworks & Tools: Hugging Face, Unsloth, PEFT (QLoRA), PyMuPDF, pdfplumber, Camelot, OpenCV, vLLM, llama.cpp (GGUF)
• Cloud & DevOps: AWS (SageMaker, ECS Fargate, Lambda, S3, SQS), Docker, Docker Compose, Git, GitLab CI/CD

Preferred Qualifications

• Strong background in computer vision, multimodal document extraction, and LLM fine‑tuning techniques.
• Proven track record of architecting cost‑effective, low‑latency deployment models on cloud infrastructure.
• Excellent technical writing, communication, and cross‑functional leadership skills.

Contact: Prabhakar T / [e-mail] / 95977 87835