Senior MLOps Engineer for GenAI Platforms

Harnham; New York (NY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Base salary + bonus

Comprehensive benefits package

Job summary

Harnham partners with a top financial services company in the NYC area seeking an experienced MLOps Engineer to scale AI automation applications and identify cost-saving opportunities. You will own generative AI, LLM and reinforcement learning infrastructure at scale and work with executive teams.

You will deploy ML models, manage real-time AI apps, and lead AI infrastructure with CI/CD pipelines, shaping technical direction and building out the AI team.

Qualifications

• 5+ years of commercial experience deploying and scaling ML/LLM models.
• Expertise in Python with TensorFlow and PyTorch for production.
• Experience building AI platforms with large datasets and real-time apps.
• Finitech domain experience is a plus and collaboration with non-technical stakeholders.
• BS or MS in Computer Science, Software/Computer Engineering or similar.

Responsibilities

• Deploy and scale ML models for the company's AI platform.
• Report to senior leadership and guide technical direction.
• Own AI infrastructure and production deployment for novel AI/LLM apps.
• Implement and productionize code using ML/LLM techniques and workflows.
• Own CI/CD pipelines for MLOps/LLMOps and distributed systems.
• Help build and scale the AI team and product across the business.
• Act as a thought leader for AI across the organization.

Skills

Python

TensorFlow/PyTorch

MLOps

Distributed systems

CI/CD

Kubernetes

Docker

Cloud platforms

Real-time AI

Fintech domain

Stakeholder management

Production deployment

Education

BS/MS in CS/SE/CE

Tools

Gitlab Pipelines

Terraform

CDK

Kubernetes

Docker

AWS

Azure

GCP

Job description

Harnham partners with a top financial services company in the NYC area seeking an experienced MLOps Engineer to scale AI automation applications and identify cost-saving opportunities. You will own generative AI, LLM and reinforcement learning infrastructure at scale and work with executive teams.

You will deploy ML models, manage real-time AI apps, and lead AI infrastructure with CI/CD pipelines, shaping technical direction and building out the AI team.