Machine Learning Engineer

Machine Learning Engineer – LLM & Agentic AI

Remote: (2 PM- 10 PM IST)

Years of Experience: 3-5 Years

Job Summary:

We are seeking a Machine Learning Engineer with hands-on experience in Large Language Models (LLMs), backend ML systems, and agentic AI solutions. This role combines building production-grade AI systems with rapidly delivering Proof of Concepts (PoCs) for clients as part of an AI incubation team.

The ideal candidate thrives in a fast-paced environment, can rapidly prototype AI solutions within 5–7 business days, and takes end-to-end ownership of delivering business outcomes.

Key Responsibilities

• Design, build, and deliver rapid AI prototypes and client-facing Proof of Concepts (PoCs) within 5–7 business days as part of an AI incubation team.
• Own the end-to-end delivery of AI solutions with a strong focus on business outcomes.
• Write high-quality, production-grade Python code to implement, optimize, and maintain machine learning pipelines, services, and tools.
• Fine-tune and adapt Large Language Models (LLMs) such as Qwen, DeepSeek, and LLaMA using:

Translation datasets

Text-based corpora, including internal policies, employee handbooks, and training materials

• Design, develop, and maintain backend ML services using Python, including:

FastAPI-based microservices

Model deployment and inference using Triton Inference Server and/or vLLM

• Develop agentic AI solutions to support:

Process optimization

Workflow automation across enterprise systems

• Build applied AI and machine learning solutions leveraging leading foundation models and platforms, including OpenAI, Gemini, and Claude, selecting the right model and architecture for each use case.
• Build and maintain data annotation pipelines to support model training and evaluation.
• Perform QA testing, validation, and performance evaluation of:

Virtual Interpreter (VI) tools

Machine learning model outputs and workflows

Required Skills & Qualifications

• Strong proficiency in Python for machine learning and backend development.
• Hands-on experience with LLM fine-tuning and NLP workflows.
• Strong knowledge of the capabilities, trade-offs, and APIs of leading foundation models, including OpenAI, Gemini, and Claude, with experience building production solutions on top of them.
• Experience deploying ML models into production environments.
• Familiarity with FastAPI, Triton Inference Server, and/or vLLM.
• Experience designing and implementing agentic AI applications and intelligent automation solutions.
• Ability to rapidly prototype AI solutions and iterate based on customer feedback.
• Strong ownership mindset with accountability for delivering high-quality solutions on time.
• Comfortable working in a fast-paced, ambiguous environment where speed, experimentation, and customer impact are key success factors.
• Experience working in innovation, incubation, consulting, or client-facing delivery teams is highly desirable.