Intern - Machine Learning Engineer

PhoenixAI; Mumbai; Hybrid; INR 2,500,000 - 4,200,000; Full time

Job summary

PhoenixAI in Mumbai, India, is seeking an AI systems engineer to fine-tune, deploy, and optimize LLMs for specialized design tasks and interactive tooling.

You will build scalable inference systems, implement RAG pipelines, and collaborate with AI researchers to turn cutting-edge experiments into production-grade infrastructure.

Proficiency in Python and PyTorch, vector search, and cloud-native architectures is essential; a hybrid work schedule is offered.

Qualifications

• Hands-on experience with LLMs including prompt tuning, fine-tuning and evaluation.
• Deep expertise in Python, PyTorch and ML tooling.
• Familiarity with LangChain/LlamaIndex and vector search concepts.
• Strong understanding of scalable ML architectures and high-availability inference.

Responsibilities

• Fine-tune, evaluate, and deploy LLMs and foundation models for specialized tasks.
• Build scalable inference systems, agentic workflows and RAG pipelines.
• Optimize model performance with batching, caching, quantization and streaming.
• Collaborate with AI scientists to operationalize experiments into production systems.
• Contribute to architecture decisions for cloud-native ML infrastructure.

Skills

LLMs

Prompt tuning

Fine-tuning

Evaluation

Python

PyTorch

LangChain

LlamaIndex

Vector search

Embeddings

RAG systems

ML infrastructure

Tools

LangChain

LlamaIndex

Job description

AI is reshaping every industry—and Physical AI is next. At PhoenixAI, you'll work at the intersection of cutting-edge ML and Robotics innovation, helping bring frontier models to production. From deploying optimized foundation models to building low-latency inference infrastructure, your work will define how engineers interact with intelligence. If you're excited to make research real and shape the future of design, this role is for you.

What you'll do

• Fine-tune, evaluate, and deploy LLMs and foundation models for specialized chip engineering tasks.
• Build scalable inference systems, agentic workflows, and RAG pipelines to support intelligent, interactive design tools.
• Optimize model performance through batching, caching, quantization, and streaming to achieve sub-second latency.
• Collaborate closely with AI scientists to operationalize experimental techniques and deliver robust, production-grade systems.
• Contribute to architecture decisions around scalable, reliable ML infrastructure in a cloud-native environment.

What You Bring

• Hands-on experience working with LLMs, including prompt tuning, fine-tuning, and evaluation.
• Deep expertise in Python, PyTorch, and the surrounding ML tooling ecosystem.
• Familiarity with orchestration frameworks and agentic workflows (e.g., LangChain, LlamaIndex).
• Strong understanding of vector search, semantic embeddings, and RAG systems.
• Solid grasp of scalable ML architecture and the principles behind high-availability inference systems.

Bonus Points

• Experience working directly with ML researchers or in applied research settings.
• Startup experience or contributions to high-velocity, cross-functional teams.
• Open-source contributions to ML tooling or infrastructure projects.
• Experience deploying models in cloud environments (e.g. AWS SageMaker, Bedrock, vLLM, or SGLang)

What it's like here

We're a fast-moving AI startup with a collaborative, high-trust culture. You'll work side-by-side with top engineers and scientists, translating cutting-edge research into real product impact. We value curiosity, speed, and precision—engineering systems that are elegant, pragmatic, and built to last. If you're passionate about bringing frontier Physical AI to the real world, you'll feel right at home.

Logistics

This position is available in Mumbai, India. We believe a mindmelt between engineers and scientists leads to our professional growth and to great products; we have a hybrid schedule.