Job description

We're looking for a Staff ML Engineer to lead the design and delivery of large-scale, production AI systems that power core products. A genuine interest in investing, public markets, and fundamental business analysis is expected. This role is for someone who combines deep machine learning expertise with strong software engineering and architectural judgment, and who is excited to solve ambiguous, high-leverage problems that shape both product capabilities and technical direction. You will work across teams to ensure our AI systems are reliable, scalable, and aligned with long-term product and infrastructure goals. You will design and operate end-to-end ML systems spanning data pipelines, training workflows, inference services, evaluation, and monitoring, while helping define how AI is applied across the company. This role is especially well suited to engineers who want to pair hands-on technical depth with cross-functional influence and long-term platform thinking. 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, infrastructure, and modeling decisions while working closely with engineering and senior leadership in a highly collaborative, low-bureaucracy environment with direct access to decision-makers. What You'll Do: · Lead the architecture and implementation of production ML and AI systems used at scale · Drive technical strategy for AI across multiple product areas · Design end-to-end systems including data pipelines, training workflows, inference services, evaluation, and monitoring · Own and deliver high-impact projects with significant ambiguity · Provide technical leadership through design reviews, mentorship, and cross-team collaboration · Identify and mitigate systemic risks in AI systems, including performance regressions, bias, and operational failure modes · Guide model lifecycle management, monitoring, and evaluation practices 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 · Deep understanding of modern ML techniques, including deep learning and representation learning · Demonstrated ability to lead technical initiatives across teams · Ability to proactively share ML knowledge and best practices, fostering a collaborative and non-siloed engineering culture · Prior experience leading or founding an AI systems team · 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 large-scale training pipelines using frameworks such as TensorFlow or PyTorch · Experience building human-in-the-loop training or evaluation workflows 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 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. 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 candidateaccessibility@versantmedia.com . 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.

Requirements

Must-haves

Lead the architecture and implementation of production ML and AI systems used at scale
Drive technical strategy for AI across multiple product areas
Design end-to-end systems including data pipelines, training workflows, inference services, evaluation, and monitoring
Own and deliver high-impact projects with significant ambiguity
Provide technical leadership through design reviews, mentorship, and cross-team collaboration
Identify and mitigate systemic risks in AI systems, including performance regressions, bias, and operational failure modes
Guide model lifecycle management, monitoring, and evaluation practices
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
Deep understanding of modern ML techniques, including deep learning and representation learning
Demonstrated ability to lead technical initiatives across teams
Ability to proactively share ML knowledge and best practices, fostering a collaborative and non-siloed engineering culture
Prior experience leading or founding an AI systems team
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 large-scale training pipelines using frameworks such as TensorFlow or PyTorch
Experience building human-in-the-loop training or evaluation workflows
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlaimachine learningpythontypescriptjava

Platform: smartrecruiters
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Paid Time Off