Machine Learning Developer

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 leadershipdriving 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.