AI / ML Engineer

Overview

Senior‑level AI/ML engineer responsible for designing, building, and operating production‑grade machine learning and generative AI solutions. This role combines hands‑on development, architectural leadership, and cross‑functional collaboration to deliver reliable, secure, and scalable AI capabilities.

Key Responsibilities

• Lead end‑to‑end AI/ML initiatives from design through deployment and monitoring
• Build and optimize LLM‑based solutions (RAG, fine‑tuning, prompt engineering, guardrails)
• Develop production ML services using APIs, containers, CI/CD, and Kubernetes
• Implement model evaluation, observability, and drift detection
• Ensure security, privacy, and responsible AI practices
• Mentor engineers and influence enterprise AI architecture and standards

Qualifications & Experience

• Bachelor’s degree and 5+ years of experience in software engineering or IT.
• Strong Python and SQL skills with solid software engineering fundamentals (testing, performance, design patterns).
• Experience across machine learning (classical models, feature engineering, time series) and deep learning using PyTorch or TensorFlow.
• Proven expertise in Generative AI, including LLMs, RAG pipelines, fine‑tuning, prompt engineering, and safety guardrails.
• Hands‑on experience with agentic AI concepts such as tool‑calling, reasoning workflows, and multi‑agent systems.
• Background in large‑scale data processing (Spark/Databricks) and streaming pipelines (Kafka).
• Familiarity with relational and NoSQL databases, data lakes, and vector search technologies.
• Experience with MLOps and platform engineering: MLflow/W&B/DVC, CI/CD, Docker, Kubernetes.
• Proficiency deploying ML systems on AWS, Azure, or GCP.
• Strong understanding of secure data handling, responsible AI, and governance.
• Demonstrated success delivering production‑grade ML/AI solutions at scale.