Computer Vision Manager

Harnham; New York (NY); Remote; USD 250,000 - 300,000; Full time

Job summary

A rapidly growing AI startup in New York is seeking a Business Manager specializing in Machine Learning and Computer Vision to lead a team. This role involves balancing engineering and leadership to develop advanced vision solutions and integrate them with AI models. Ideal candidates will have over 7 years in the field, strong management experience, and excellent communication skills. This position offers a competitive salary range of $250,000–$300,000, with options for remote work.

Qualifications

• 7+ years of professional experience in computer vision or machine learning.
• At least 2 years in a management role.
• Strong hands-on experience with modern ML frameworks.
• Proven track record of deploying production-scale systems.

Responsibilities

• Lead and mentor a team of computer vision and ML engineers.
• Define and execute the technical roadmap for vision-focused initiatives.
• Design and deliver advanced computer vision solutions.
• Drive integration of vision models with LLMs and VLMs.

Skills

Computer vision

Deep learning

Applied machine learning

Leadership

Communication skills

Tools

PyTorch

TensorFlow

Job description

Business Manager - Machine Learning, LLMs, Generative AI & MLOps at Harnham

Computer Vision Manager

$250,000–$300,000 base + equity + benefits

Remote

About the Organization

Harnham is working with a rapidly growing AI startup addressing complex real-world problems with state-of-the-art technology. Their focus is on building intelligent systems that integrate computer vision, multimodal models, and generative AI to redefine how industries function. Backed by top-tier investors and already working with enterprise clients, this is an opportunity to join a high-growth company where your contributions will directly shape mission-critical workflows.

About the Role

They are looking for a Manager to lead a growing Computer Vision Engineering team. This position is perfect for someone who can balance hands-on engineering with guiding and mentoring a team, setting the technical vision while driving delivery of production-ready AI solutions. In this role, you’ll spearhead the development of advanced vision pipelines—including diffusion, detection, segmentation, transformers, and 3D vision—and work on integrating them with large language models (LLMs) and vision-language models (VLMs) to build robust, real-world multimodal systems.

Responsibilities

• Lead, mentor, and support a team of computer vision and ML engineers, fostering collaboration, innovation, and professional growth
• Define and execute the technical roadmap for vision-focused initiatives
• Design and deliver advanced computer vision solutions spanning detection, segmentation, classification, 3D perception, diffusion and multimodal pipelines
• Drive the integration of vision models with LLMs and VLMs to enable reasoning and automation
• Partner with cross-functional teams to transition cutting-edge research into scalable, production-ready systems
• Stay at the forefront of research in transformers, diffusion models, and multimodal agents, applying breakthroughs to real-world applications

Experience

• 7+ years of professional experience in computer vision, deep learning, or applied machine learning
• At least 2 years in a management role with demonstrated success directly managing teams or projects
• Strong hands-on experience with modern ML frameworks such as PyTorch or TensorFlow
• Proven track record of deploying production-scale computer vision systems
• Familiarity with vision transformers, multimodal models (e.g., CLIP, BLIP, Flamingo), and generative AI
• Excellent communication skills with the ability to engage both technical and non-technical stakeholders
• Based in the U.S. (NYC preferred, though remote is an option)
• Contributions to open-source CV/AI initiatives or publications at leading conferences are a plus

How to Apply

Please register your interest by sending your résumé to Tim Jonas via the Apply link on this page.