Machine Learning Engineer - Artificial Intelligence/Deep Learning

Role Overview:

We are looking for a Machine Learning Engineer to design, develop, deploy, and maintain production-grade machine learning and AI systems. The role requires strong Python, ML fundamentals, and experience taking models from experimentation to production.

Responsibilities:

• Build and train machine learning and deep learning models.
• Develop end-to-end ML pipelines for training, evaluation, deployment, and monitoring.
• Work with structured, unstructured, image, or text datasets.
• Deploy scalable ML inference APIs and services.
• Optimize models for latency, accuracy, scalability, and cost.
• Implement model monitoring, versioning, retraining, and MLOps workflows.
• Collaborate with backend, data, product, and engineering teams.
• Evaluate new ML/GenAI technologies and integrate them where appropriate.

Tech Stack:

• Languages: Python
• Frameworks: PyTorch, TensorFlow
• APIs: FastAPI, Flask
• Infrastructure: AWS, Azure, GCP, Docker, Kubernetes
• Tools: SQL, Git, Linux, MLflow

Required Qualifications:

• 3 - 6 years of software engineering / machine learning experience.
• Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Data Science, or a related field.

Preferred Qualifications:

• Experience building production-scale AI systems.
• Experience with vector databases and distributed systems.
• Experience optimizing model inference using ONNX, TensorRT, vLLM, or similar technologies.
• Familiarity with transformers, embeddings, LLMs, RAG, or Generative AI is a plus.