Be an early applicantLess than 25 applicants

Company

SandboxAQ · 7 hours ago

Principal Machine Learning Engineer - AQMed

United States

Full-time

Remote

Lead/Staff

$225K/yr - $368K/yr

10+ years exp

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Artificial Intelligence (AI)Cyber Security

H1B Sponsor Likely

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Responsibilities

Hone your technical leadership by applying hard-won practical experience in deep learning to tackle challenging yet rewarding problems at the forefront of medical science, while collaborating with a world-class team.

Design, train, and fine-tune state-of-the-art deep learning architectures that seamlessly integrate multimodal data for robust and scalable solutions.

Harness cutting-edge AI techniques to uncover novel biomarkers, combining insights from the latest research, experimental data, and explainability frameworks to drive groundbreaking clinical applications.

Contribute to building and refining pipelines that power a sophisticated custom AI stack, delivering precise predictions, actionable insights, and user-friendly visualizations tailored for medical and scientific innovation.

Develop tools for explainable AI and integrate findings into production systems.

Build dashboards and tools to communicate progress and performance using AWS and other 3rd party tools.

Adeptly present insights to cross-functional teams as well as internal and external stakeholders, targeting your communication to the particular audience and anticipating the questions and proof points that speak best to their perspective.

Mentor junior team members, fostering a collaborative and innovative team environment with people management potential in the future.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Deep LearningMachine LearningPythonAWSStatistical ExpertiseData WranglingVersion Control (git)Time Series DataBiomedical ModelsExplainable AIHyperparameter TuningClusteringGraph NetworksGenerative ModelingContrastive LearningTransfer LearningLarge Models on GPUsSynthetic DataBuilding DashboardsAmbiguity ManagementCross-functional Collaboration

Required

10+ years as a data scientist or MLE, including experience working with time series data, biomedical models (especially cardiac), and training AI models on very large datasets.

Masters or PhD in computer science, data science, mathematics, physics, AI or a related field.

Developed and deployed state-of-the-art deep learning models to production for real-world applications, especially in MedTech.

Proficient in advanced DL/ML frameworks, with a focus on self-supervised methods like contrastive learning, generative modeling, masked modeling, graph networks, and clustering.

Skilled in hyperparameter tuning, explainability, and transfer learning.

Proficient in Python and using versioning control systems (e.g., git), show high-quality code standards.

Strong foundation in statistics, probability, and data wrangling from varied sources.

Comfortable with AWS, docker, and scalable batching pipelines.

Skilled at bridging technical, clinical, and business perspectives by presenting insights tailored to diverse stakeholders.

Thrive in ambiguity, take ownership, balance competing priorities effectively, and excel at translating a compelling vision into technical reality.

Preferred

Experience training large models on GPUs.

Working with LLMs.

Using synthetic data to augment small real-world datasets.

Benefits

Annual discretionary bonuses

Equity

Competitive salaries

Stock options depending on employment type

Generous learning opportunities

Medical/dental/vision

Family planning/fertility

PTO (summer and winter breaks)

Financial wellness resources

401(k) plans

Company

SandboxAQ

SandboxAQ is an enterprise SaaS company that provides AI and quantum solutions.

Founded in 2016

Palo Alto, California, USA

51-200 employees

https://www.sandboxaq.com

H1B Sponsorship

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Trends of Total Sponsorships

2023 (1)

2022 (4)

2021 (2)

2020 (8)