AI/ML Engineer

Job Post: AI/ML Engineer (Full-Time / Contract)

Location: Mohali
Experience Level: Mid–Senior / Expert
Compensation: Competitive (based on experience)

Contact: +91-9872993778

About the Role

We are looking for a highly skilled AI/ML Engineer to design, build, and deploy production-grade machine learning systems. You will work on everything from data preprocessing and model development to LLM-powered applications, MLOps pipelines, and scalable backend integrations. This role is ideal for someone who enjoys ownership, architectural thinking, and solving real-world problems with AI.

ResponsibilitiesMachine Learning & Deep Learning

• Develop, train, and optimize ML/DL models (classification, detection, NLP, generative models).
• Work with frameworks such as TensorFlow, PyTorch, Keras, Scikit-Learn.
• Implement evaluation, fine-tuning, A/B testing, and model improvement strategies.

LLMs & Generative AI

• Build RAG pipelines using vector databases (Pinecone, Qdrant, pgvector, Chroma).
• Create LLM agents with tool-calling, reasoning, memory, structured outputs.
• Integrate models such as GPT-4/5, Llama-3, Mistral, Qwen, or custom fine-tuned models.
• Implement prompt engineering, orchestration (LangChain, LangGraph), and workflow automation.

Data Engineering

• Build data ingestion, preprocessing, transformation, and annotation pipelines.
• Work with REST APIs, cloud storage, ETL/ELT pipelines, and distributed systems.

MLOps & Deployment

• Deploy models to AWS / GCP / Azure / Docker / Kubernetes environments.
• Set up CI/CD pipelines, monitoring, logging, and automated retraining loops.
• Optimize model performance, latency, GPU utilization, and cost efficiency.

Backend Integration

• Build microservices in Python / FastAPI / Flask / Node.js.
• Integrate ML models into production APIs and customer-facing systems.

Requirements

• 3–8+ years experience in ML, deep learning, or applied AI engineering.
• Strong command of Python, NumPy, Pandas, and ML/DL frameworks.
• Hands-on experience with LLMs, embeddings, vector databases, and prompt engineering.
• Experience deploying ML systems in production environments.
• Strong understanding of cloud services: AWS (S3, Lambda, EC2, ECS, SageMaker) or equivalent.
• Ability to work independently, communicate clearly, and deliver high-quality results.
• Familiarity with MLOps tools: Docker, Kubernetes, GitHub Actions, Airflow, MLflow, etc.

Nice to Have

• Experience fine-tuning LLMs or training custom models on domain-specific datasets.
• Knowledge of computer vision (YOLO, OpenCV, segmentation models).
• Familiarity with distributed training, optimization, and GPU clusters.
• Experience with OCR tools (PaddleOCR, Azure Document Intelligence, Tesseract).
• Understanding of reinforcement learning or agentic workflows.

Job Type: Full-time

Work Location: In person