AI Engineer

About Eucloid :

Eucloid is a premier Data/AI organization that leverages state-of-the-art AI and Data Science technologies to deliver high-impact projects.

We create business-critical solutions for Fortune-100 clients and industry leaders across various sectors, including Hi-tech, D2C, Healthcare, SaaS, and Retail.

Our deep partnerships with leading platforms like Databricks, Google Cloud Platform, and Adobe enable us to build and deploy cutting-edge data products and massive-scale data platforms.

Our world-class team, composed of professionals from top-tier institutes and leading global organizations, thrives in an environment that prioritizes growth, innovation, and excellence.

Job Description :

We are looking for an AI Engineer with strong AI/ML and GenAI systems expertise to build and produce next-generation AI systems.

This role is for someone who can go beyond using frameworks - someone who understands how models and AI systems work internally, can design the architecture around them, evaluate them rigorously, and take a prototype all the way to a scalable, production-grade system.

Role & Responsibilities :

AI/ML & Multimodal AI :

- Strong first-principles understanding of Machine Learning, Deep Learning and Computer Vision

- Deep understanding of LLMs and Vision-Language Models (VLMs) - tokenization/encoding, vision & language representations, multimodal alignment and how semantic information is fused

- SFT for LLMs/VLMs, PEFT/LoRA and fine-tuning strategies

- Model optimization: quantization (AWQ, INT4, HQQ), distillation, batching and inference optimization

- vLLM and high-performance model serving

- Reward modelling, custom/verifiable rewards, DPO, RLHF and GRPO

- Hands-on experience with PyTorch, Hugging Face Transformers and TRL

RAG, Retrieval & AI Agents :

- Build advanced RAG / GraphRAG / VisionRAG systems

- Retrieval & ranking : BM25, semantic retrieval, hybrid search, vector databases

- Understand and implement RRF, MRR, Recall, Precision, F1, RAGAS and other evaluation approaches

- Query optimization using HyDE, query expansion and rewriting

- Agentic systems using LangGraph, LangChain, CrewAI, Agno or equivalent

- Understanding of MCP, its communication/transport mechanisms, tool calling and context engineering

- Structured output generation, schema validation and reliable tool execution

Evaluation & ML Engineering :

- Build evaluation harnesses, automated testing and benchmarking frameworks

- Design golden datasets, taxonomies and evaluation datasets

- Perform model benchmarking, error analysis and root-cause analysis of model failures

- Design data preprocessing, transformation and ML pipelines

- Understand model quality vs. latency vs. memory vs. cost trade-offs

- Experience with distributed ML systems using Ray or equivalent.

Production AI Systems & Architecture :

- Design end-to-end AI/ML system architectures

- Taking rapid prototypes - robust production systems

- Build Python/FastAPI microservices and REST APIs

- Docker/containerization, webhooks and SSE

- CI/CD, Git/GitHub and production engineering practices

- Design scalable pipelines involving queues, asynchronous processing and distributed workloads

- Hands-on exposure to multi-GPU training/inference is highly desirable

Background and Skills :

- Undergraduate Degree in any quantitative discipline such as engineering or science from a Top-Tier institution. MBA is a plus.

- Minimum 3 years of relevant experience in GEN AI.

- Strong hands-on experience in AI/ML infrastructure, cloud platforms, and production-grade ML systems.

- Prior experience working with AWS or GCP cloud services, particularly services such as AWS Bedrock, SageMaker, EC2, S3, SQS, Lambda, ECR, EKS, CloudWatch, or GCP Vertex AI.

- Experience with GPU infrastructure, CUDA, multi-GPU environments, and distributed training is required.

- Hands-on experience with containerized and Kubernetes-based environments, including Docker and Kubernetes.

- Experience working with LLMs, model training, fine-tuning, inference, and deployment using modern ML frameworks and tools.

- Experience building and deploying scalable APIs and ML services in production environments.

- Strong understanding of Linux, networking/API fundamentals, REST APIs, and CI/CD practices.

Location : Chennai, Hybrid work mode (4 days Work from Office and 1 day Work from Home)

Rewards :

- Attractive compensation

- Rapid and clear growth path

- Interaction with industry experts

- On job training and skill development

Eucloid offers an expedited growth path along with a compensation package which is among the best in the industry