Senior AIML Engineer

Orcapod Consulting Services; Bengaluru; Hybrid; INR 3,500,000 - 6,500,000; Full time

Job summary

Orcapod Consulting Services seeks a Senior AI/ML Engineer to lead advanced AI initiatives in Bengaluru. You will own end-to-end AI/ML solutions, from data exploration to production deployments, with a focus on scalable model development and robust statistics.

You will work across open- and closed-source LLM ecosystems, design GraphRAG pipelines, and implement RLHF/RLAIF-based alignment while collaborating with cross-functional teams to deliver production-ready AI systems.

Qualifications

• 10+ years in applied AI/ML with a solid background in statistics and production-grade deployments.
• PhD or Masters in Computer Science, Machine Learning, or a related field.

Responsibilities

• LLM & Fine-Tuning: Train and fine-tune LLMs across open-source (Qwen, LLaMA, Mistral) and closed-source (OpenAI, Gemini, Anthropic) platforms.
• GraphRAG & Retrieval: Architect GraphRAG pipelines, knowledge graphs, and semantic retrieval with advanced doc segmentation.
• Infrastructure & Scaling: Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU/multi-node setups.
• Alignment & Reinforcement Learning: Apply RLHF, RLAIF, PPO, DPO, and SFT to align models to domain goals.
• Production Deployment: Collaborate with cross-functional teams to deliver production-ready AI solutions.

Skills

Python

SQL

EDA

PyTorch

Transformers

State-space models

Agentic workflows

FAISS

Weaviate

Milvus

BGE

E5

SimCSE

LoRA

QLoRA

axolotl

DSPy

GEPA

Azure ML

AWS

Education

PhD or Masters in Computer Science / ML

Tools

NCCL

InfiniBand

Job description

Role Overview

• Role: Senior AI/ML Engineer
• Experience Required: 10+ years in applied AI/ML with a solid background in statistics and production-grade deployments.
• Education: PhD or Masters degree in Computer Science, Machine Learning, or a related field.

Key Responsibilities

• LLM & Fine-Tuning: Drive end-to-end training and fine-tuning of Large Language Models across both open-source ecosystems (e.g., Qwen, LLaMA, Mistral) and closed-source platforms (e.g., OpenAI, Gemini, Anthropic).
• GraphRAG & Retrieval: Architect and implement GraphRAG pipelines, knowledge graphs, and semantic retrieval systems with advanced document segmentation.
• Infrastructure & Scaling: Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU and multi-node training.
• Alignment & Reinforcement Learning: Apply techniques such as RLHF, RLAIF, PPO, DPO, and SFT to align model behavior with domain-specific goals.
• Production Deployment: Collaborate with cross-functional teams to translate complex business requirements into production-ready AI solutions.

Required Technical Stack & Expertise

• Core Languages & Tools: Advanced Python coding, SQL, database queries, and Exploratory Data Analysis (EDA).
• Frameworks & Architecture: PyTorch, transformer architectures, state space-based models, and agentic workflows.
• Specialized Skills:
  • Vector databases and semantic search (FAISS, Weaviate, Milvus)
  • Embedding models (BGE, E5, SimCSE)
  • Fine-tuning tools and frameworks (LoRA, QLoRA, axolotl, DSPy, GEPA)
  • Cloud platforms (Azure ML and/or AWS)