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Full timeTechnology

Machine Learning Engineer (Mid-Level)

CleraSan Francisco🇺🇸United StatesPosted Oct 22, 2026

Why this role stands out

Accelerate your career at Clera by building high-impact AI solutions within a collaborative, fast-moving team that values technical innovation and professional growth. This role is perfect for a skilled engineer who thrives on owning the full ML lifecycle and wants to shape the future of recruiting technology. Apply today to leverage your expertise in a dynamic environment where your contributions directly influence production-grade systems.

Quick overview

SeniorityMid Senior
Employment typeFull Time
Work modeOn Site
LocationSan Francisco, United States
Posted17 hours ago
DockerGCPAWSScikit-learnA/B TestingPyTorchPythonTensorFlowKubernetesMachine Learning

Job description

About the Role

Join a small, fast-moving team building AI-powered talent and recruiting technology. You will design, deploy, and maintain machine learning systems across the full lifecycle, helping turn product needs into reliable production capabilities.

What You'll Do

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

  • Build end-to-end ML pipelines, from data preprocessing through model serving and monitoring.

  • Work with product and engineering partners to translate business requirements into ML solutions.

  • Debug and improve models in production using monitoring data 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

  • A degree and at least 3 years of professional machine learning or software engineering experience, including building and deploying production ML systems.

  • Strong understanding of model selection, evaluation metrics, feature engineering, and validation techniques.

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

  • Experience implementing production pipelines for data preprocessing, model serving, and monitoring.

  • Experience maintaining ML systems at scale with tools or platforms such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.

  • Experience with production A/B testing or experimentation frameworks.

  • Background working in fast-moving product environments and iterating on ML systems based on production feedback.

Compensation & Benefits

Base salary: $140,000 USD annually. Visa sponsorship information was not provided.

Location

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

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