This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

If you're interested sign up to Dex to apply. Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

The role

This isn't another early-stage AI experiment. We're talking about a team with a long history of shipping production AI, processing vast and complex financial datasets that underpin global capital markets. They build search, discovery, and workflow products on top of advanced models, serving hundreds of thousands of users who depend on real-time, reliable systems.

You'll join a specialized MLOps team, owning the tooling and infrastructure that keeps this model development lifecycle reliable, fast, and observable. This role is about designing and building the core systems for continuous training, inference, and monitoring at a scale few companies can offer. It's not about ad-hoc scripting or managing a handful of models; it's about architecting robust, high-SLA platforms for a critical, high-volume environment.

The work

Design and build continuous training pipelines that enable rapid iteration and confident deployment of ML models.
Architect and implement inference infrastructure capable of handling high throughput and low latency demands for critical user-facing products.
Develop comprehensive monitoring workflows and define strict SLAs around latency, throughput, and resource usage (CPU, GPU, memory, network).
Collaborate with AI Platform teams to operationalize models end-to-end, ensuring seamless integration from research to production.
Partner directly with ML engineers building customer-facing products to understand their needs and deliver robust, scalable MLOps solutions.

What You Bring

5+ years of professional experience as a strong Python developer, with hands-on work in production ML environments.
Experience operating or building ML infrastructure using cloud-native tooling like Kubernetes and Argo Workflows.
Working knowledge of ML frameworks such as PyTorch, ONNX, or DeepSpeed, and an understanding of operational demands at scale.
Experience with at least one major cloud provider (AWS, GCP, or Azure) and strong reasoning about infrastructure decisions.
Solid CS fundamentals (data structures, algorithms, system design) and a track record of delivering production-quality code.

Why apply through Dex

This kind of MLOps role, operating at immense scale and criticality, is rare and often hard to find through traditional channels. Apply through Dex to cut through the noise: get a proper briefing on this specific opportunity, understand the nuances, and skip the cold application process. We connect you directly to roles that truly match your profile, saving you time and effort in a competitive market.

If you're interested, sign up to Dex to apply - https://jobs.meetdex.ai/jobs/f6c6d7fe-da06-4733-809f-fb1e24889611

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Senior MLOps Engineer - Artificial Intelligence (up to $290k)

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