Senior Machine Learning Engineer at Unlearn AI

San Francisco, California, United States

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$165,000 – $200,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial IntelligenceIndustries

Requirements

Candidates must possess an M.S. degree in computer science, engineering, physics, mathematics, or a related field. Strong software engineering skills, collaborative development experience, and fluency in Python and its ecosystem are essential. A solid understanding of ML architecture fundamentals, including linear algebra, statistics, and optimization, is required, along with deep experience in ML frameworks like PyTorch and/or TensorFlow.

Responsibilities

The Senior Machine Learning Engineer will design and implement machine learning models for disease progression characterization and prediction. Responsibilities include implementing, evaluating, and fine-tuning novel model architectures, translating conceptual ML approaches into performant code, and improving ML infrastructure for training and inference efficiency. The role also involves developing software libraries for scalable ML workflows, measuring and reporting on ML system health, and staying current with state-of-the-art ML engineering tools and approaches.

Skills

Machine Learning

Generative AI

Clinical Trials

Software Development

Experimentation

Team Collaboration

Unlearn AI

Creates AI-driven digital twins for healthcare

About Unlearn AI

Unlearn.AI creates digital twins of patients using artificial intelligence, which are virtual replicas that simulate potential health outcomes. This technology allows healthcare providers to predict how a patient's health may change over time, leading to more informed treatment decisions. The primary clients include healthcare providers and pharmaceutical companies, who can use these digital twins in clinical trials to simulate control groups, potentially speeding up drug development and approval processes. Unlearn.AI differentiates itself by offering a unique simulation technology that reduces the need for actual human control groups, which can save time and resources. The company's goal is to enhance decision-making in patient care and drug development through precise health outcome predictions.

San Francisco, CaliforniaHeadquarters

2017Year Founded

$127.1MTotal Funding

SERIES_CCompany Stage

AI & Machine Learning, HealthcareIndustries

51-200Employees