Senior MLOps Engineer

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 is partnering with a top financial services company in the NYC area, which is looking for an experienced MLOps Engineer. This person will be at the forefront of scaling AI automation applications for new ways at identifying cost-saving opportunities. You'll partner with executive teams across the company and own generative AI, LLM and reinforcement learning application infrastructure deployment at scale.

RESPONSIBILITIES

• You will be responsible for machine learning model deployment and scalability for the company's AI platform
• You will report directly to senior leadership and work closely on technical direction
• Own AI infrastructure and quickly build into production, particularly focusing on novel AI and LLM applications
• You will implement and design code and build out to production using various machine learning and LLM techniques, owning machine learning workflow operations and distributed systems
• Own CI/CD pipelines for MLOps / LLMOps
• You will play an integral role of building out the AI team and scaling out its product
• Act as a thought leader role for AI across the business

SKILLS AND EXPERIENCE

• 5+ years of commercial experience preferred with a focus on deploying and scaling machine learning and LLM models
• Expertise in Python (TensorFlow, PyTorch) for production-grade work
• Commercial experience building novel AI platforms with large datasets
• History of working with and managing real-time AI applications in production settings
• Fluency with low-latency distributed systems is preferred
• Cloud experience in AWS, Azure or GCP
• DevOps experience with CI/CD pipelines required; Gitlab Pipelines, CDK or Terraform
• Container experience with Kubernetes, Docker or similar
• History of working on models from concept to production / end-to-end / 0-1
• Domain experience in fintech or similar a plus
• History of partnering with non-technical stakeholders required
• Experience owning projects directly preferred
• BS or MS degree in Computer Science, Software Engineering, Computer Engineering or similar

BENEFITS

• The compensation package contains a base salary, bonus and a comprehensive benefits package.

KEY TERMS

Artificial Intelligence | Generative AI | GenAI | Machine Learning | ML Engineer | Engineering | Deployment | Production | Real Time | Enterprise | Statistics | Mathematics | Financial Services | Banking | Python | Anomaly Detection | Fintech | Agentic AI | AI Agents | MLOps | ML Operations | Deployment | Deploy | Production | CI/CD | Container | Docker | Gitlab Pipelines | Terraform | Kubernetes