Job Description

Machine Learning Engineer – Applied AI Systems

San Francisco, CA – On-site

$170k–$250k + equity

A venture-backed AI company is expanding its engineering group and looking for a Machine Learning Engineer to help push forward a new generation of decision-support products used in complex, data-heavy environments.

The team builds systems that analyse large, unstructured datasets and surface insights that help organisations make high-stakes choices more consistently. You’ll join a small group of engineers and researchers working on applied ML problems that combine pattern recognition, anomaly detection, language modelling and real-time data interpretation.

This is a hands-on engineering role where you’ll prototype, train, evaluate and productionise models that directly shape the product experience.

What you’ll work on

• Designing and implementing ML pipelines for processing a wide variety of semi-structured inputs.
• Training and adapting large language models to handle classification, extraction and reasoning tasks.
• Developing methods to identify irregularities, inconsistencies and unusual patterns within customer-supplied data.
• Improving the performance, latency and reliability of deployed models at scale.
• Collaborating with software engineers to integrate new capabilities into customer-facing features.
• Exploring new approaches in multimodal modelling, retrieval-augmented generation and adaptive learning systems.

Who you might be

• Someone with professional experience in ML engineering, data science, applied research or similar.
• Confident programming in Python and fluent with at least one modern deep learning toolkit.
• Comfortable working with messy, real-world data rather than clean academic datasets.
• Experience with information extraction, language models, anomaly detection or data quality modelling is valuable.
• Interested in joining a company where the ML team has genuine influence over product direction.
• Enjoys experimentation, iteration and solving problems that don’t have an obvious starting point.

(No strict requirement on years — strength of experience matters more than time served.)

Why this is different

• You’ll work on technically challenging problems where accuracy genuinely matters.
• The company is scaling quickly and investing heavily in expanding its AI group.
• You’ll collaborate closely with product and engineering leadership, not sit in a research silo.
• The environment is fast-moving, with opportunities to own projects end-to-end.
• Generous salary, equity and benefits package.

Location & Work Style

• On-site in San Francisco to support a highly collaborative engineering culture.
• Hybrid flexibility may be available for senior hires already living in the Bay Area.

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