AI/ ML Engineer (Fashion Startup/ 3-5 years)

PeopleGene; Bengaluru; On-site; INR 1,500,000 - 2,200,000; Full time

Job summary

PeopleGene is seeking an AI engineer to design, train, and optimize Generative AI solutions for enterprise use. You will work with LLMs, multimodal models, and build scalable data pipelines for training, fine-tuning, and inference.

You will implement guardrails, monitor performance, latency, and cost, and collaborate with business, consulting, and product teams to translate problems into robust GenAI architectures and success metrics.

Qualifications

• Bachelor’s or Master’s degree in CS, DS, AI, or related field.
• Proficiency with Python or PyTorch.
• Experience with image generation models (Flux, SDXL, Diffusers).
• Hands-on experience with LLMs, transformers, embeddings, and vector databases.
• Proficiency in GenAI frameworks (LangChain, LlamaIndex, Haystack, HuggingFace).
• Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning).
• Experience designing multi-agent systems, including orchestration and distributed reasoning.
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
• Experience in fast-paced startup environment (preferred).
• 3D deep learning and large-scale point cloud processing is a plus.

Responsibilities

• Design, train, and evaluate Generative AI models for enterprise use cases.
• Develop and optimize prompt engineering, RAG pipelines, agents, and fine-tuning workflows.
• Design, develop, and optimize a multi‑agent agentic framework for autonomous collaboration across specialized agents.
• Work with OpenAI, Anthropic, LLaMA, Mistral, and other LLMs.
• Implement guardrails, safety mechanisms, and hallucination mitigation techniques.
• Partner with business, consulting, and product teams to identify GenAI use cases.
• Translate business problems into clear GenAI solution architectures and success metrics.
• Create solution blueprints, prototypes, and POCs to demonstrate business value.
• Design and manage data pipelines for AI training, fine-tuning, and inference.
• Build scalable, secure, and cost-efficient GenAI systems for production environments.
• Collaborate with engineering on deployment, monitoring, and retraining strategies.
• Monitor model performance, latency, cost, and drift in production.
• Ensure responsible, ethical, and compliant use of Generative AI.
• Implement explainability, auditability, and traceability mechanisms where required.
• Address data privacy, IP protection, and regulatory constraints (e.g., GDPR).
• Define and enforce AI best practices, standards, and usage guidelines.

Skills

Python

PyTorch

LLMs

Transformers

Embeddings

Vector Databases

LangChain

LlamaIndex

Haystack

HuggingFace

LoRA

PEFT

Instruction Tuning

MLOps

CI/CD

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field

Tools

Flux

SDXL

Diffusers

Job description

• Design, train, fine-tune, and evaluate Generative AI models (LLMs, multimodal models) for enterprise use cases.
• Develop and optimize prompt engineering, RAG pipelines, agents, and fine-tuning workflows.
• Design, develop, and optimize a multi‑agent agentic framework that enables autonomous, domain‑aware collaboration across specialized agents.
• Work with open-source and commercial LLMs (OpenAI, Anthropic, LLaMA, Mistral, etc.).
• Implement guardrails, safety mechanisms, and hallucination mitigation techniques.
• Partner with business, consulting, and product teams to identify, evaluate, and prioritize GenAI use cases.
• Translate business problems into clear GenAI solution architectures and success metrics.
• Create solution blueprints, prototypes, and POCs to demonstrate business value.
• Design and manage data pipelines for AI training, fine-tuning, and inference.
• Build scalable, secure, and cost-efficient GenAI systems for production environments.
• Collaborate with engineering teams on deployment, monitoring, and retraining strategies.
• Monitor model performance, latency, cost, and drift in production.
• Ensure responsible, ethical, and compliant use of Generative AI.
• Implement explainability, auditability, and traceability mechanisms where required.
• Address data privacy, IP protection, and regulatory constraints (e.g., GDPR).
• Define and enforce AI best practices, standards, and usage guidelines.

Good to have:

• Prior 3-5 years of experience in data science, ML engineering, or AI development.
• Expertise with Python or Pytorch.
• Experience with image generation models (Flux, SDXL, Diffusers)
• Strong hands-on experience with LLMs, transformers, embeddings, and vector databases.
• Proficiency in Python and GenAI frameworks (LangChain, LlamaIndex, Haystack, Hugging Face).
• Experience with fine-tuning techniques (LoRA, PEFT, instruction tuning).
• Experience designing multi‑agent systems, including orchestration, coordination, and distributed reasoning.
• Familiarity with MLOps tools, CI/CD pipelines, and model monitoring.
• Familiarity with 3D deep learning and large scale point cloud processing is a plus.
• Experience working in fast paced startup environment (preferred).
• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.