AI / ML Engineer

We are looking for a skilled AI/ML Engineer with hands-on experience in machine learning, statistical modeling, generative AI, and production deployment. The ideal candidate should be proficient in Python, LLMs, RAG, AI agents, and MLOps, with the ability to develop scalable AI solutions that deliver measurable business outcomes.

Responsibilities:

• Develop and deploy machine learning models for regression, classification, forecasting, and anomaly detection.
• Build AI/ML solutions using Python, Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Develop Generative AI applications using LLMs, RAG, prompt engineering, tool calling, and agent workflows.
• Optimize models and AI applications for accuracy, cost, latency, and scalability.
• Use AI coding tools such as Claude Code, Cursor, or similar tools to improve development productivity.
• Work with SQL databases, including PostgreSQL, SQL Server, or Oracle.
• Deploy and monitor AI/ML models using Git, CI/CD, Docker, Kubernetes, and cloud platforms, preferably AWS.
• Integrate AI solutions with business applications, APIs, and enterprise systems.
• Conduct code reviews, mentor junior engineers, and establish engineering best practices.
• Collaborate with senior stakeholders on requirements gathering, effort estimation, project tracking, and status reporting.
• Follow AI governance, data privacy, security, and responsible AI practices.

Requirements:

• Skills include Python, Pandas, NumPy, and Scikit-learn.
• Machine learning and statistical modeling expertise.
• Experience with generative AI, LLMs, RAG, and prompt engineering.
• Experience with AI agents, tool calling, and agent workflows.
• Proficiency in TensorFlow or PyTorch.
• SQL and relational database experience.
• MLOps, Git, CI/CD, Docker, and production deployment experience.
• Hands-on experience deploying real-world AI/ML solutions.

Nice To Have:

• AWS cloud services experience.
• Experience with MCP servers and agentic tooling.
• Familiarity with Claude Code, Cursor, or similar AI coding tools.
• Experience with Kubernetes and model monitoring.
• Technical leadership and stakeholder management experience.
• Proven experience in production AI/ML deployments, measurable business outcomes, and end-to-end generative AI application development.