Senior ML Engineer – AI Platform

About StockStory VERSANT is an independent, publicly traded company that brings together powerhouse brands such as CNBC, MS NOW (formerly MSNBC), USA Network, Oxygen, E!, SYFY, and Golf Channel along with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine.

StockStory, now part of CNBC under VERSANT, is building the next generation of AI-powered equity research for individual investors. This is a chance to build products that can shape how millions of consumers understand markets and make investing decisions.

We offer the best parts of a startup environment - small team, high ownership, fast execution, and room to experiment - with the backing and stability of VERSANT, an independent publicly traded media company.

The work spans cutting-edge LLMs / ML, large-scale data systems, financial reasoning, and research tooling, with opportunities to apply ideas from functional programming and graph-based systems where they create real advantage.

You will be joining a team of exceptional engineers, analysts, and investors working at the intersection of AI and public markets. A particularly rare part of this role is the level of direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design. For an ambitious AI engineer, it is an unusual opportunity to work with cutting-edge technology and advanced data systems while learning firsthand how sophisticated investors analyze businesses and markets.

StockStory, now part of CNBC under VERSANT, is building the next generation of AI-powered equity research for individual investors. This is a chance to build products that can shape how millions of consumers understand markets and make investing decisions.

We offer the best parts of a startup environment - small team, high ownership, fast execution, and room to experiment - with the backing and stability of VERSANT, an independent publicly traded media company.

As a Senior ML Engineer, working in a team of 15 you will work on both an existing AI product with real user impact and greenfield projects with significant room for exploration.

The work spans cutting-edge LLMs / ML, large-scale data systems, financial reasoning, and research tooling, with opportunities to apply ideas from functional programming and graph-based systems where they create real advantage.

You will be joining a team of exceptional engineers, analysts, and investors working at the intersection of AI and public markets. A particularly rare part of this role is the level of direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design. For an ambitious AI engineer, it is an unusual opportunity to work with cutting-edge technology and advanced data systems while learning firsthand how sophisticated investors analyze businesses and markets.

What You’ll Do:

This role is for engineers who enjoy turning machine learning and AI capabilities into reliable product systems used by real customers at scale. It is especially well suited to people who want to work across the full stack of applied ML, from data pipelines and model training to inference, evaluation, and production operations.

• You will design, build, and operate core components of our AI platform: production-grade ML systems, LLM workflows, and supporting infrastructure that power core user experiences for individual investors.
• This role sits within a small and growing, high-caliber team where individuals are expected to operate with a high degree of ownership and autonomy, contributing directly to core product, engineering, and modeling decisions while working closely with senior leadership in a highly collaborative, low-bureaucracy environment with direct access to decision-makers.
• Design, implement, and maintain production ML and AI systems used at scale
• Own end-to-end delivery of AI features from data pipelines and training workflows to inference and monitoring· Contribute to architectural decisions and technical standards and mentor peers to elevate ML quality
• Solve complex technical problems with moderate ambiguity and strong business impact
• Participate in code reviews and incident retrospectives to improve system quality and reliability …