---
title: Mid Level Machine Learning Engineer at Clera
description: Clera is hiring for the Mid Level Machine Learning Engineer role in San Francisco,
  CA. Pays $140K per year. See the full description and apply.
type: job
url: https://www.foundrole.com/jobs/mid-level-machine-learning-engineer-at-clera-01a1db38-6c02-7d1d-9204-a177b351777c
date: 2026-11-14T20:34:48Z
og_description: Join Clera as Mid Level Machine Learning Engineer in San Francisco, CA. Pays $140K
  per year. Full-time, on-site role.
og_image: https://www.foundrole.com/og/sigypb.png
breadcrumbs:
  - label: Home
    url: https://www.foundrole.com/
  - label: Search
    url: https://www.foundrole.com/jobs
---

| | |
|---|---|
| **Company** | Clera |
| **Location** | San Francisco, CA |
| **Salary** | $140K/yr |
| **Type** | Full Time |
| **Posted** | Nov 14, 2026 |

## Is this job real?

**Ghost job check:** B · Low risk. Probably a real opening.

## Visa sponsorship

- **H-1B:** No H-1B sponsorship on record for Clera.
- **E-Verify:** No E-Verify enrollment on record for Clera.

## Pay for similar jobs

Most similar jobs pay $151,000 – $260,000 a year (median $205,000).

## Description

### About the Role

Build and operate production machine learning systems at an early-stage AI recruiting and talent technology company. You will own work across the ML lifecycle, partnering with product, engineering, and domain experts to deliver models that support the core product.

### What You'll Do

- Design, train, and evaluate machine learning models for production use cases.

- Build end-to-end ML pipelines, including data preprocessing, model serving, and monitoring.

- Partner with product and engineering teams to turn business needs into ML solutions.

- Debug and improve production model performance using monitoring and real-world feedback.

- Write maintainable code and contribute to ML infrastructure and tooling.

- Participate in code reviews and share knowledge with teammates.

### What We're Looking For

- At least 3 years of professional machine learning or software engineering experience, including building and deploying production ML systems.

- Strong ML fundamentals, including model selection, evaluation, feature engineering, and validation.

- Proficiency in Python and hands-on experience with TensorFlow, PyTorch, or scikit-learn.

- Experience implementing end-to-end ML pipelines and maintaining deployed systems at scale.

- Familiarity with MLOps and cloud platforms or tools such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.

- Experience with production A/B testing or experimentation, and debugging models based on operational feedback.

- Background in a startup or fast-moving, product-focused environment, plus completed university studies and professional employment after graduation.

### Compensation & Benefits

Base salary starts at $140,000 USD annually. The upper end of the range was not provided. Visa sponsorship policy was not provided.

### Location

On-site in San Francisco, California, United States.
## Skills

- Feature Engineering
- Data Preprocessing
- Cloud Computing
- Debugging
- Scikit-learn (Machine Learning Library)
- AWS SageMaker
- MLOps
- A/b Testing
- Code Review
- Python
- Google Vertex AI
- Docker
- Kubernetes
- Google Cloud Platform (Gcp)
- Machine Learning
- Recruitment
- Model Serving
- TensorFlow

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