Senior ML Engineer - AI Platform

About the role

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
• Support the team's overall technical growth
• Identify and mitigate risks in AI systems, including performance regressions, bias, and operational issues
• Use and improve model lifecycle management, monitoring, and evaluation frameworks
• Hands-on experience with neural networks, including CNNs, RNNs, Transformers, or other deep learning architectures
• Background in classical and modern NLP techniques such as tokenization, sequence labeling, language modeling, embeddings, text classification, and information extraction
• Experience with training pipelines using frameworks such as TensorFlow or PyTorch
• Experience building human-in-the-loop training or evaluation workflows
• A genuine interest in investing, public markets, and fundamental business analysis is expected.

Requirements

• Bachelor's degree in Computer Science or equivalent practical experience
• Minimum of 5 years of experience in software engineering with a focus on machine learning or AI systems
• Experience building and operating production ML systems
• Strong proficiency in Python, TypeScript, or Java
• Proven experience with LLMs, ranking or recommendation systems, search, or applied NLP
• Solid understanding of modern ML techniques, including deep learning and representation learning
• Experience contributing to system design and technical decision-making

Location: Hybrid 3 days in office

At CNBC Headquarters in Englewood Cliffs, NJ, you'll have access to great perks and amenities:

• Sweat it out -- Free onsite fitness center with state-of-the-art equipment, plus daily group classes
• Eat up -- Gourmet cafeteria with daily specials plus soup and salad bars
• Extras -- Dry cleaning, shoe shining and sneak peeks
• Don't have a car? No problem! We offer free shuttle transportation to and from multiple locations in Manhattan, Brooklyn, Hoboken and Jersey City

Additional information

In addition to these benefits, employees in this group will be joining at a time of meaningful and continued investment in data, technology, and product development, with the opportunity to contribute to a growing team within CNBC that is expected to scale significantly over time, offering meaningful exposure to senior leadership and the ability to influence how the platform evolves.

Additional Information

Versant

Media is committed to fair and equitable compensation practices. We include a good faith pay range for each position to comply with applicable state and local pay transparency laws and to promote equity across our organization. Actual compensation will be based on factors such as the candidate's skills, qualifications, experience, and location and may include additional forms of compensation and benefits such as health insurance, retirement plans, paid time off, etc.

Versant

Media is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at VERSANT via-email, the Internet, or in any form and/or method without a valid written Statement of Work in place for this position from VERSANT's Talent Acquisition team will be deemed the sole property of VERSANT. No fee will be paid in the event the candidate is hired by VERSANT as a result of the referral or through other means.