Senior ML Engineer - AI Platform

Versant View all jobs
Englewood Cliffs, NJ, United States
22 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$140,000.0 - $175,000.0
Working hours
Regular working hours

Tech stack

Java (Programming Language) Artificial Intelligence Amazon Web Services Artificial Neural Networks Big Data Code Review Data Systems Information Extraction Python (Programming Language) Machine Learning Language Modeling Natural Language Processing
+16 more
Software Product Management Software Architecture Recommender Systems Tensorflow Software Engineering TypeScript Pytorch Large Language Models Deep Learning AI Platforms Kubernetes Information Technology Machine Learning Operations Functional Programming Document Classification Data Pipelines

Job description

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. Qualifications 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., 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. By clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website’s terms and privacy policy apply, Lead Machine Learning Engineer (MLOps, KServe + building Kubernetes Clusters, PyTorch, TensorFlow on AWS) As a Capital One Machine Learning Engineer (MLE), you’ll be part of an Agi…

  • 1 day ago +

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

Benefits & conditions

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.

About the company

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., 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., 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

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.

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