Senior Gen AI Engineer

SciSpace; Bengaluru; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

SciSpace is seeking a Senior Research Scientist to design and deploy scalable ML systems and APIs. You will work on transformer-based LLM deployments, data pipelines, and collaboration with researchers to bring AI-enabled solutions to scale.

The role emphasizes building robust ML infrastructure, optimizing algorithms, and documenting systems for cross-functional teams. Strong Python skills and experience with Gen AI are essential.

Qualifications

• 3+ years of experience with designing multi-component systems.
• Strong Python programming skills.
• SQL knowledge and database design basics.
• Solid understanding of testing fundamentals.
• Strong communication skills.
• Experience in managing and executing technology products.
• Understanding of Gen AI-based ML approaches.
• Experience building agentic architectures using langgraph or similar libraries.

Responsibilities

• Design, develop, and maintain scalable ML systems, including APIs.
• Deploy ML models and transformer-based LLMs into production.
• Collaborate with infra teams to support ML workflows.
• Create robust data pipelines for datasets.
• Work with data scientists and researchers to integrate ML solutions.
• Continuously optimize ML algorithms and systems.
• Develop and maintain documentation for ML systems, APIs, and data pipelines.

Skills

Python

Communication

Gen AI approaches

Langgraph

ML systems design

SQL basics

Tools

Docker

AWS

GCP

Azure

Job description

We are looking for an insatiably curious, always learning Senior Research Scientist. You could get a chance to work on the most important and challenging problems at scale. As a software engineer dedicated to developing Gen AI-based ML systems, you will be involved in the deployment of ML models, building ML systems and pipelines to ensure reliable systems are deployed at scale to provide value for researchers. This is an engineering-dominated role, but the candidate should have basic knowledge of ML, especially NLP Transformer-based (LLM) models, to be able to handle the systems better.

Responsibilities

• ML System Development: Design, develop, and maintain scalable and efficient machine learning systems, including writing ML services and APIs.
• Model Deployment: Implement and manage the deployment of machine learning models, including transformer-based LLMs, into production environments, ensuring reliability and scalability.
• Infrastructure Management: Collaborate with infrastructure teams to optimise and manage the underlying systems supporting machine learning workflows.
• Data Pipeline Creation: Create robust and efficient data pipelines for collecting, processing, and preparing datasets for machine learning models.
• Collaboration: Work closely with data scientists, researchers, and cross-functional teams to integrate ML solutions into existing software infrastructure.
• Performance Optimisation: Continuously optimise and improve the performance of machine learning algorithms and systems.
• Documentation: Develop and maintain documentation for machine learning systems, APIs, and data pipelines to ensure clarity and ease of use for team members.

Requirements

• 3+ years of experience, including working on designing multi-component systems.
• Strong grasp of one high-level language like Python.
• General awareness of SQL and database design concepts.
• Solid understanding of testing fundamentals.
• Strong communication skills.
• Should have prior experience in managing and executing technology products.
• Decent understanding of various Gen AI-based ML approaches.
• Experience in building agentic architectures using langgraph or similar libraries.

Bonus

• Prior experience working with high-volume, always-available web applications.
• Experience working with the cloud.
• Knowledge of cloud platforms such as AWS, GCP, or Azure.
• Experience with deploying small and big open source LLMs in production environments using containerization tools like Docker.
• Experience in distributed systems.
• Experience working with a Start-up is a plus point.