Additionalinformation

Additional Information

As part of our selection process, external candidates may be required to attend an in-person interview with a VERSANT Media employee at one of our locations prior to a hiring decision. VERSANT Media's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to [email protected].

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.

Companydescription

Company Description

VERSANT (Nasdaq: VSNT) is an industry-changing media and entertainment business and home to trusted brands that shape culture, inform audiences, and build lasting connections. It operates across four core markets: political news and opinion, business news and personal finance, golf, and sports and genre entertainment. These markets are served through a powerful portfolio of iconic and innovative brands, including CNBC, MS NOW, USA Network, Golf Channel, Oxygen, E!, SYFY, and Versant's sports division USA Sports, along with complementary digital assets including Fandango, Rotten Tomatoes, GolfNow and GolfPass.

Jobdescription

Job Description

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, 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.

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We're looking for a highly capable Senior ML Engineer to join our team to build the next generation of AI-powered equity research.

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.

Qualifications

What We're Looking For:

• Bachelor’s degree in Computer Science or equivalent practical experience
• Minimum of 8 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

• Bachelor’s degree in Computer Science or equivalent practical experience
• Minimum of 8 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