Walk-in | Ai Ml Engineer

Experis (Austria); Chennai, Bengaluru; Híbrido; INR 2.000.000 - 4.000.000; Jornada completa

Descripción de la vacante

Experis (Austria) is seeking an AI/ML Engineer with a strong blend of full-stack software engineering and applied AI to design, build, and optimize Generative AI-powered applications. You will integrate LLMs into enterprise apps and deliver secure, production-grade solutions with business impact.

The role covers RAG, agentic workflows, and scalable AI services across OpenAI, Azure AI, and open-source models. Strong collaboration with product and data teams is essential.

Formación

• Bachelor’s or Master’s in CS, Engineering, AI or related field.
• 4–10 years of Applied AI, ML, software engineering and digital transformation.
• Proficient in Python; Java and React preferred.
• Experience with PyTorch, NLP, APIs, and cloud AI services.

Responsabilidades

• Develop AI-powered features using LLMs for chat, summarization, and data extraction.
• Design RAG solutions with embeddings, vector search, and retrieval optimization.
• Build AI services with OpenAI, Azure AI, and open-source LLMs.
• Create agentic AI workflows and multi-agent automation.
• Tune models with prompts, guardrails, evaluation and fine-tuning.
• Work with vector databases like FAISS, Pinecone, pgvector.
• Collaborate with product, data, and engineering teams on AI solutions.
• Participate in architecture discussions and code reviews.

Conocimientos

Python programming

Deep learning

NLP/LLM concepts

Communication of AI topics

Educación

Bachelor's or Master's in CS/Engineering/AI

Herramientas

PyTorch

OpenAI APIs

FastAPI

Flask

Streamlit

REST APIs

Docker

Kubernetes

Spark

Pinecone/FAISS

React JS

Java

SQL

Descripción del empleo

Role & responsibilities

Detailed JD Below:

AI/ML Engineer

Team: Engineering / AI Platform

Employment Type: Full-Time

About the Role

We are seeking an AI/ML Engineer with a strong blend of Full-Stack Software Engineering and Applied AI expertise to design, build, and optimize Generative AI-powered applications. The role involves developing scalable AI solutions, integrating LLMs into enterprise applications, implementing agentic workflows, and delivering secure, production-grade solutions that drive business value.

Key Responsibilities

• Develop and enhance AI-powered features such as chatbots, summarization, knowledge search, and data extraction using LLMs.
• Design and implement RAG (Retrieval-Augmented Generation) solutions, including data preprocessing, embeddings, vector search, and retrieval optimization.
• Build and integrate AI services using OpenAI, Azure AI, and open-source LLMs.
• Develop agentic AI workflows, multi-agent frameworks, and intelligent automation solutions.
• Improve model performance, reliability, and accuracy through prompt engineering, evaluation, guardrails, and fine-tuning techniques.
• Work with vector databases such as FAISS, Pinecone, and pgvector.
• Optimize AI applications for latency, throughput, scalability, and cost efficiency using caching, batching, quantization, and model optimization techniques.
• Collaborate with product, data, and engineering teams to deliver high-quality AI solutions.
• Participate in architecture discussions, code reviews, and knowledge-sharing initiatives.

Required Qualifications

• Bachelors or Master’s degree in Computer Science, Engineering, AI, or a related field.
• 4–10 years of experience in Applied AI, Machine Learning, Software Engineering, and Digital Transformation.
• Strong experience designing and deploying enterprise-scale AI solutions using Generative AI, LLMs, AI Agents, and Intelligent Automation.
• Proficiency in Python (mandatory) and experience with Java and React JS preferred.
• Hands-on expertise in PyTorch, SQL, OpenAI APIs, FastAPI, Flask, Streamlit, REST APIs, Docker, and modern application architectures.
• Strong understanding of machine learning fundamentals, deep learning, statistics, optimization, feature engineering, and model development.
• Experience with NLP/NLU, semantic search, transformer architectures, embeddings, and model interpretability.
• Knowledge of Azure, AWS, and GCP cloud AI services.
• Ability to communicate technical AI concepts effectively to business and leadership stakeholders.

Preferred Skills

• MLOps, React JS , Java Backend , CI/CD for ML, model monitoring, lifecycle management, Kubernetes, Docker, and JFrog.
• Experience deploying ML models to production environments.
• Distributed ML and scalable data platforms (e.g., Spark).
• Multimodal AI, including Computer Vision and Speech Recognition (ASR).
• Knowledge of AI governance, Responsible AI, security, compliance, and model lifecycle management.
• Experience in healthcare, life sciences, payer/provider, or other regulated industries.
• Experience leading Agile teams and collaborating across cross-functional stakeholders