Machine Learning Engineer

iSpace Software Solutions India Private Limited; Hyderabad, Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

iSpace Software Solutions India Private Limited seeks an AI Engineer is an ML engineer responsible for building and optimizing machine learning models, RAG systems, and verifiable ML systems transforming how we search and analyze complex medical and insurance data. This role focuses on production-grade systems, not data science or purely research.

The candidate will design data pipelines, embedding models, and end-to-end ML workflows, ensuring scalability, safety, and governance.

Qualifications

• BS in Computer Science (focus on machine learning/AI) or a related field.
• 3+ years of industry experience with Gen AI technologies.
• Experience with containerization, Kubernetes, and cloud-native ML technologies such as Kubeflow.
• Experience with CI/CD pipelines and automated testing.

Responsibilities

• Data engineering: Design and optimize systems capable of processing large volumes of data in both batch and real-time.
• Design, implement, and optimize retrieval-augmented generation (RAG) systems that leverage the latest LLM technologies to deliver highly relevant search results at scale.
• Develop and refine embedding models, vector databases, and retrieval mechanisms that maximize search relevance while minimizing latency and operational costs.
• Create robust evaluation frameworks to measure quality, continuously improve our LLM-based solution based on user feedback and performance metrics.
• Build and optimize machine learning models and verifiable ML systems that transform how we search and analyze complex medical and insurance data.
• Build and optimize production-ready systems that are scalable and can handle large amounts of data.
• Build and optimize agentic systems that can reason and make decisions.
• Develop machine learning models in healthcare and insurance settings with the highest standards for safety and quality.
• Stay on top of AI and ML security and governance requirements.

Skills

Data engineering

RAG systems

LLM technologies

Production ML

Agentic systems

Python

ML frameworks

Containerization

Kubernetes

Kubeflow

CI/CD

Automated testing

Healthcare data

Insurance data

Education

BS in Computer Science (ML/AI focus)

Tools

Kubeflow

Kubernetes

Containerization

CI/CD pipelines

Python tooling

Job description

The AI Engineer is an ML engineer who is responsible for building and optimizing machine learning models, retrieval-augmented generation (RAG) systems, and verifiable ML systems that transform how we search and analyze complex medical and insurance data. This role requires a deep understanding of machine learning, LLM technologies, data science, and software engineering. This is an ML-engineering role and not a data science role, which means you should be comfortable building production-ready systems. This is not a research role.

ESSENTIAL JOB RESPONSIBILITIES & KEY PERFORMANCE OUTCOMES

• Data engineering: Design and optimize systems capable of processing large volumes of data in both batch and real-time.
• Design, implement, and optimize retrieval-augmented generation (RAG) systems that leverage the latest LLM technologies to deliver highly relevant search results at scale.
• Develop and refine embedding models, vector databases, and retrieval mechanisms that maximize search relevance while minimizing latency and operational costs.
• Create robust evaluation frameworks to measure quality, continuously improve our LLM-based solution based on user feedback and performance metrics.
• Build and optimize machine learning models and verifiable ML systems that transform how we search and analyze complex medical and insurance data.
• Build and optimize production-ready systems that are scalable and can handle large amounts of data.
• Build and optimize agentic systems that can reason and make decisions.
• Develop machine learning models in healthcare and insurance settings with the highest standards for safety and quality.
• Stay on top of AI and ML security and governance requirements.

REQUIRED QUALIFICATIONS

• BS in Computer Science (concentration on machine learning/AI), Engineering, Statistics, or a related field
• At least three (3) years of industry experience and specifically with some of the recent Gen AI technologies.
• Experience with containerization, Kubernetes, and cloud-native ML technologies such as Kubeflow.
• Experience with CI/CD pipelines and automated testing.

High level of proficiency with Python and several ML frameworks.