Job Description

Position Summary: We are hiring a highly technical individual contributor to push the limits of our computer vision and machine learning capabilities. This is a high-impact, hands-on role for a research-minded engineer who wants to build and ship models. Much of the work involves large-scale visual understanding, extracting structured signals from imagery and reasoning about the real-world context behind a photograph, but we care more about deep ML/CV ability than any one problem area and welcome strong generalists.

Responsibilities:

Build, train, evaluate, and deploy computer vision and multimodal models, taking them from early prototype through to production

Design systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoning

Train and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scale

Work with vision- models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasks

Develop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategies

Optimize models for inference latency and throughput using techniques like distillation, quantization, and GPU acceleration

Read current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production code

Implement efficient, scalable data pipelines and inference infrastructure

Develop high-performance tooling in ML and data engineering

Requirements:

Experience building, training, evaluating, and deploying ML models in production

Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models

Strong software engineering ability to build and maintain complex systems and work with large-scale datasets

Ability to solve open-ended problems and quickly learn new domains

Comfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraints

BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience

Nice to have:

Experience inferring structured, real-world attributes from images

Experience training models on large-scale, real-world image datasets

Familiarity with vision- models (VLMs)

Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production code

Experience building LLM or VLM pipelines and the evaluation frameworks to measure their performance

Experience in an ML role at a growth-stage startup

Publications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV)

Benefits

Medical, Dental, Vision, STD and LTD Plans

FSA - Medical and Dependent Care

EAP and wellness programs

13 Paid Holidays

Unlimited PTO

Flexible work environment - 100% remote

401(k) plan

Senior Machine Learning Engineer in United

Senior Machine Learning Engineer in United

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