AI / ML Engineer

Samsung; Bengaluru; On-site; INR 1,400,000 - 2,000,000; Full time

Job summary

Samsung in Bengaluru is seeking a skilled AI/ML Engineer to design, develop and deploy production-grade ML solutions. You will work with Python, Pandas, NumPy, Scikit-learn and deep learning frameworks to deliver measurable business outcomes.

You will lead deployment pipelines using Git, CI/CD, Docker, Kubernetes and AWS, implement generative AI apps with LLMs, RAG, and agent workflows, and mentor junior engineers while partnering with senior stakeholders on requirements and timelines.

Qualifications

• Proficient in Python for ML and data processing.
• Strong experience with Pandas, NumPy and Scikit-learn.
• Hands-on with TensorFlow or PyTorch for model development.
• Experience deploying AI/ML solutions in production environments.
• Familiarity with MLOps concepts, CI/CD and containerization.
• Knowledge of SQL databases and cloud platforms like AWS.

Responsibilities

• Develop and deploy ML models for regression, classification, forecasting and anomaly detection.
• Build AI/ML solutions using Python and common ML libraries.
• Develop generative AI apps using LLMs, RAG, prompt engineering, tool calls and agent workflows.
• Optimize models for accuracy, cost, latency and scalability.
• Leverage AI coding tools to improve productivity and code quality.
• Work with SQL databases and deploy/monitor models via Git, CI/CD, Docker, Kubernetes and AWS.
• Integrate AI solutions with business apps and enterprise systems.
• Mentor juniors, conduct code reviews and establish engineering best practices.
• Collaborate with stakeholders on requirements, estimates and project status.
• Uphold AI governance, data privacy, security and responsible AI practices.

Skills

Python

Pandas

NumPy

Scikit-learn

Tools

TensorFlow

PyTorch

Claude Code

Cursor

Git

CI/CD

Docker

Kubernetes

AWS

SQL

Job description

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.