Senior Software Engineer (Machine Learning- MLops)

Are you passionate about working with cutting-edge technologies, tackling complex data integration challenges, and enabling seamless operations in multi-cloud environments? Join our team and play a pivotal role in shaping the future of Data ETL for Large Language Models (LLMs)!

We specialize in building ETL workflows for Retrieval-Augmented Generation (RAG) systems, empowering businesses to unlock the potential of unstructured data. With several trusted partners and an expanding vision, we are looking to add a new team member to grow our capabilities.

You will:

• Collaborate on integrating various databases, applications, and model providers, including AWS Bedrock.
• Build and maintain robust ETL pipelines for unstructured data across multi-cloud environments (Azure, AWS, and potentially GCP).
• Work closely with cross-functional teams to deliver scalable, secure, and efficient solutions.
• Contribute to infrastructure as code (IaC) practices using Pulumi and ArgoCD.
• Provide public-facing on-call support as needed, ensuring seamless operations and addressing customer concerns promptly.

Key Responsibilities

• Develop and deploy scalable solutions for integrating LLMs into RAG workflows.
• Enhance multi-cloud deployment capabilities to support Azure, AWS, and other platforms.
• Design and implement MLOps pipelines and automation for efficient model lifecycle management.
• Serve as a critical point of contact for public-facing on-call support, addressing technical issues effectively.
• Work in close collaboration with teams across UI, API layers, and infrastructure components.

What you’ll need to succeed in this role:

• Proven expertise in Kubernetes and Python: Demonstrated experience building and managing containerized applications.
• Strong MLOps background: Hands-on experience in developing and maintaining MLOps pipelines.
• Prior on-call experience: Ability to manage and resolve incidents in public-facing roles with professionalism.
• Excellent communication skills: Proficiency in written and spoken English to effectively interact with external and internal stakeholders.
• Multi-cloud experience: Familiarity with Azure and AWS is essential; GCP experience is a plus.
• Infrastructure as Code (IaC): Proficiency with tools like Pulumi and ArgoCD.