Machine Learning Engineer / Data Scientist (MLE + DS)

Job Title: Senior Machine Learning Engineer / Data Scientist (Generative AI & MLOps)

Job Details

• Experience: 5-7 Years
• Employment Type: Full-Time
• Work Mode: Remote / Work From Home
• Job Location: Remote, India
• Joining: Immediate Joiners Preferred

Job Summary

We are looking for an experienced Senior Machine Learning Engineer / Data Scientist with 810 years of experience in developing, deploying, and maintaining production-grade AI and Machine Learning solutions. The ideal candidate should have strong expertise in Python, Machine Learning, MLOps, Kubeflow, Generative AI, Large Language Models (LLMs), Claude AI, and Model Context Protocol (MCP).

The candidate will be responsible for designing end-to-end AI/ML solutions, building automated ML pipelines, developing LLM-powered applications, implementing AI-driven automation workflows, and deploying scalable solutions in cloud environments.

This role requires strong technical expertise, hands-on development experience, excellent communication skills, and the ability to work directly with clients to understand business requirements and deliver effective AI solutions.

Key Responsibilities

1. Design, develop, test, and deploy end-to-end Machine Learning and Data Science solutions.
2. Build, manage, and optimize production-grade ML pipelines using MLOps best practices.
3. Develop, orchestrate, and monitor Machine Learning workflows using Kubeflow.
4. Develop Generative AI applications using Large Language Models, including Claude and other relevant LLM platforms.
5. Build AI-powered assistants, intelligent agents, and enterprise automation solutions.
6. Implement Model Context Protocol (MCP) servers, clients, and tool integrations for AI applications.
7. Develop AI Skills and reusable capabilities to support task automation and intelligent workflows.
8. Implement Retrieval-Augmented Generation (RAG) pipelines, embeddings, semantic search, and vector-based retrieval.
9. Integrate AI models with REST APIs, databases, enterprise applications, and external systems.
10. Perform model evaluation, performance optimization, testing, monitoring, and lifecycle management.
11. Deploy and manage AI/ML applications using cloud platforms, Docker, Kubernetes, and CI/CD pipelines.
12. Collaborate with engineering, product, and business teams to translate requirements into scalable technical solutions.
13. Engage directly with clients to gather requirements, conduct technical discussions, present solutions, and provide implementation guidance.
14. Identify opportunities to automate business processes using AI, Machine Learning, and intelligent agents.
15. Mentor junior engineers, conduct code reviews, and contribute to engineering standards and best practices.

Required Technical Skills

Machine Learning and Data Science

• Strong proficiency in Python programming.
• Hands-on experience with Machine Learning algorithms and statistical modelling.
• Experience with Scikit-learn, TensorFlow, and/or PyTorch.
• Knowledge of data preprocessing, feature engineering, model training, evaluation, and optimization.
• Experience developing and deploying production-grade ML solutions.

MLOps and Kubeflow

• Hands-on experience with Kubeflow Pipelines and ML workflow orchestration.
• Experience building automated, reproducible, and scalable ML pipelines.
• Understanding of model deployment, versioning, monitoring, and lifecycle management.
• Knowledge of CI/CD practices for Machine Learning applications.
• Experience with Docker, Kubernetes, and containerized application deployment.

Generative AI and LLMs

• Practical experience developing applications using Large Language Models.
• Hands-on experience with Claude AI and/or other LLM platforms.
• Strong understanding of prompt engineering, context management, structured outputs, and tool calling.
• Experience developing AI assistants, LLM-based applications, and intelligent automation workflows.
• Understanding of Retrieval-Augmented Generation (RAG), embeddings, and semantic search.
• Knowledge of AI agent architectures and multi-step workflow execution.

Claude AI, MCP, and AI Automation

• Experience integrating Claude AI into applications and enterprise workflows.
• Understanding of Model Context Protocol (MCP) architecture and its client-server model.
• Experience building or integrating MCP servers, tools, and resources.
• Knowledge of AI Skills, reusable instructions, and task-oriented automation capabilities.
• Experience integrating AI systems with APIs, databases, and external tools.
• Ability to design secure, reliable, and maintainable AI-powered automation workflows.

Cloud and Deployment

• Experience with AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of Docker, Kubernetes, and container orchestration.
• Experience with CI/CD pipelines and automated deployment processes.
• Understanding of application monitoring, logging, scalability, and production troubleshooting.

API Integration and Software Engineering

• Experience developing and integrating REST APIs.
• Strong understanding of software engineering principles and code quality.
• Experience working with SQL/NoSQL databases.
• Knowledge of Git, testing frameworks, debugging, and application performance optimization.

Preferred Skills

• Experience with vector databases such as Pinecone, Qdrant, Weaviate, Chroma, or FAISS.
• Familiarity with LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI, or similar frameworks.
• Experience implementing advanced RAG architectures and retrieval optimization.
• Knowledge of LLM evaluation, observability, guardrails, and AI security.
• Experience with workflow automation and enterprise integration platforms.
• Familiarity with model serving, model monitoring, and ML lifecycle management tools.
• Experience building AI agents that interact with external tools and enterprise systems.

Communication and Leadership Skills

• Excellent verbal and written communication skills.
• Strong client-facing experience and stakeholder management capabilities.
• Ability to independently lead technical discussions and requirement-gathering sessions.
• Strong analytical thinking, problem-solving, and decision-making skills.
• Ability to explain complex AI/ML concepts to technical and non-technical stakeholders.
• Experience mentoring junior team members and collaborating with cross-functional teams.

Candidate Profile

• 5-7 years of relevant experience in Machine Learning, Data Science, AI Engineering, or related fields.
• Strong hands-on experience in Python, Machine Learning, and production AI systems.
• Practical experience with Kubeflow, MLOps, Generative AI, and LLM-based applications.
• Experience with Claude AI, MCP integrations, and AI-driven automation.
• Proven ability to design, develop, and deploy scalable AI/ML solutions.
• Prior experience working with enterprise customers is preferred.
• Immediate joiners or candidates available to join at short notice are preferred.
• Candidates must be comfortable working remotely and collaborating with distributed teams.

What We Offer

• Opportunity to work on enterprise-grade AI, Machine Learning, and Generative AI solutions.
• Exposure to modern AI technologies, LLM integrations, and intelligent automation.
• Opportunity to contribute to end-to-end AI solution architecture and implementation.
• Fully remote working environment.
• Collaborative engineering culture with opportunities for technical ownership.

Application Instructions

Interested candidates can apply with an updated resume highlighting their experience in Python, Machine Learning, Kubeflow, MLOps, Generative AI, Claude AI, MCP, and production AI/ML deployments.

Candidates with relevant project experience and strong client-facing communication skills are encouraged to apply.