# Founding ML Engineer, Computer Vision (Object Detection) at Clera

Founding ML Engineer, Computer Vision (Object Detection) at Clera in New York. Remote, full-time, paying $200k–$260k. Posted October 28, 2026.

- Company: Clera
- Location: New York
- Workplace: Remote
- Job type: Full-time
- Pay: $200k–$260k
- Experience: 5+ years
- Posted: 2026-10-28
- Apply: https://jobs.ashbyhq.com/clera/b638b702-daf6-47d4-8393-4cf11e84991b/application
- Source: https://jobmagic.ai/jobs/founding-ml-engineer-computer-vision-object-detection-clera-sgza9f

## Requirements

- At least 5 years of applied computer vision experience, including shipping systems to production at meaningful scale.
- Hands-on experience with fine-grained or instance-level recognition, distinguishing visually similar products where near-misses are not acceptable.
- Production experience fine-tuning and deploying vision transformers or CNNs using PyTorch or TensorFlow.
- Experience adapting foundation vision models to specific use cases, and designing evaluation frameworks that measure progress beyond loss metrics.
- Experience with calibrated prediction confidence and ownership of model serving decisions, including latency, cost, and reliability.
- Clear written and verbal communication skills, and comfort leading technical direction on an open-ended problem. Active learning, human-in-the-loop labeling, low-latency APIs, and early-stage startup experience are useful.

## Description

### About the Role

Join an early-stage marketplace company as its first machine learning engineer focused on computer vision. You will lead the design and production deployment of fine-grained item identification models, helping users identify products accurately and reliably from photos.

### What You'll Do

- Design computer vision architecture for identifying items by brand, model, edition, and variant, adapting foundation vision models to a specific catalog.

- Define category-level accuracy standards and build calibrated confidence scoring so the product can communicate uncertainty appropriately.

- Create feedback loops that use model errors to guide labeling priorities in partnership with the labeling team.

- Set priorities between expanding category coverage and improving accuracy in existing categories.

- Own the model serving path from research through production, balancing latency, cost, and reliability at scale.

- Explain model capabilities, limitations, and technical tradeoffs to company stakeholders.

### What We're Looking For

- At least 5 years of applied computer vision experience, including shipping systems to production at meaningful scale.

- Hands-on experience with fine-grained or instance-level recognition, distinguishing visually similar products where near-misses are not acceptable.

- Production experience fine-tuning and deploying vision transformers or CNNs using PyTorch or TensorFlow.

- Experience adapting foundation vision models to specific use cases, and designing evaluation frameworks that measure progress beyond loss metrics.

- Experience with calibrated prediction confidence and ownership of model serving decisions, including latency, cost, and reliability.

- Clear written and verbal communication skills, and comfort leading technical direction on an open-ended problem. Active learning, human-in-the-loop labeling, low-latency APIs, and early-stage startup experience are useful.

### Compensation & Benefits

Base salary: $200,000 to $260,000 annually. Visa sponsorship is not available.

### Location

Hybrid role based in New York, New York.