Machine Learning Engineer (Mid-Level)

Clera

San Francisco, CA

On-site

Who this role is best for

Geared toward mid-level professionals comfortable with end-to-end ML pipeline development, working in a collaborative, on-site environment in San Francisco.

Best fit for

Candidates with 3+ years of hands-on production ML experience and a background in building scalable AI systems.
— “At least 3 years of professional experience in machine learning or software engineering, including hands-on production ML work”
Individuals who have worked in product companies or startups and are familiar with MLOps and cloud infrastructure.
— “Familiarity with MLOps and cloud tools such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker”

Things to consider

On-site requirement in San Francisco may not be suitable for remote-only candidates.
— “On-site in San Francisco, California, United States”
The role expects collaboration across product and engineering teams, which may require strong communication skills.
— “Collaborate with product and engineering teams to develop ML solutions for business needs”

How to stand out

Highlight experience with model deployment and monitoring in your resume and interviews.
— “Monitor, debug, and optimize production model performance using real-world feedback”
Emphasize your background in building end-to-end ML pipelines, including preprocessing and serving.
— “Build end-to-end ML pipelines, from data preprocessing through model serving and monitoring”
Showcase your work in production A/B testing or experimentation to demonstrate adaptability in fast-moving environments.
— “Experience with production A/B testing or experimentation, and comfort working in fast-moving environments”

Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

reliable models and features
production ML pipelines
real-world feedback
maintainable code
ML infrastructure and tooling

Typical background

3+ years of professional experience in machine learning or software engineeringdegree in a substantive ML role at a product company or startup

Skills & requirements

Required

Machine LearningModel EvaluationModel DeploymentProduction ML PipelinesMlopsCloud Tools

Preferred

A/B TestingFast-moving EnvironmentsModel ServingMonitoring

Stack & domain

Machine LearningPythonTensorFlowPyTorchscikit-learnMlopsAWS SagemakerGCP Vertex AIKubernetesDockerA/B TestingCollaborationCommunicationProblem-solvingTeamworkAdaptabilityAIRecruitingSoftware Engineering

About the role

Original posting from Clera via Ashby

ABOUT THE ROLE
As a Machine Learning Engineer, you'll build and deploy production machine learning systems for an AI-powered recruiting platform. You'll work across the ML lifecycle, partnering with product and engineering to turn business needs into reliable models and features.
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.
Collaborate with product and engineering teams to develop ML solutions for business needs.
Monitor, debug, and optimize production model performance using 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 experience in machine learning or software engineering, including hands-on production ML work and employment after graduation.
A completed degree and experience in a substantive ML role at a product company or startup.
Strong ML fundamentals, including model selection, evaluation, feature engineering, and validation.
Proficiency in Python and practical experience with TensorFlow, PyTorch, or scikit-learn.
Experience building and maintaining production ML pipelines, including preprocessing, serving, and monitoring.
Familiarity with MLOps and cloud tools such as AWS SageMaker, GCP Vertex AI, Kubernetes, or Docker.
Experience with production A/B testing or experimentation, and comfort working in fast-moving environments.
COMPENSATION & BENEFITS
Salary starts at $140,000 USD annually. Equity and visa sponsorship details were not provided.
LOCATION
On-site in San Francisco, California, United States.

Source: Clera careers (Ashby)