Principal Machine Learning Engineer, SandboxAQ
AQMed
$225-368k
AI and quantum computing solutions
Open for applications
AI and quantum computing solutions
201-500 employees
Open for applications
$225-368k
201-500 employees
Company mission
To develop commercial products for telecom, financial services, healthcare, federal government, computer security and other computationally-intesive sectors.
Role
Who you are
- Experience: 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
- Achievements: You’ve developed and deployed state-of-the-art deep learning models to production for real-world applications, especially in MedTech. You’ve shipped products, bringing practical, seasoned knowledge to navigate challenges and deliver results
- Deep Learning and Machine Learning Expertise: 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. Bonus points for experience training large models on GPUs, working with LLMs, and using synthetic data to augment small real-world datasets
- Engineering capabilities: You’re proficient in Python and using versioning control systems (e.g., git), show high-quality code standards, and actively collaborate with other scientists and researchers reviewing PRs and writing scalable, maintainable code
- Statistical Expertise: You have a strong foundation in statistics, probability, and data wrangling from varied sources
- Cloud Proficiency: Comfortable with AWS, docker, and scalable batching pipelines
- Cross-functional Collaboration: Skilled at bridging technical, clinical, and business perspectives by presenting insights tailored to diverse stakeholders. Builds intuitive dashboards and visualization tools to drive shared understanding, alignment, and actionable decisions across teams
- Mindset: You thrive in ambiguity, take ownership, balance competing priorities effectively, and excel at translating a compelling vision into technical reality
What the job involves
- The AQMed team is seeking a Principal Machine Learning Engineer (MLE) with deep expertise and industry experience to tackle complex challenges in advancing cardiac diagnostics
- This role will add a critical perspective in identifying optimal approaches to working with data
- The Principal MLE will not only be able to work with rich data sets (both synthetic and real clinical study data) but will also work at the cutting edge of architecting, training, and productizing Deep Learning (DL) and Machine Learning (ML) models
- This is an opportunity to bring your expertise to a small but dynamic team that thrives on research, iteration, and collaboration
- You will also work closely with external partners to refine and advance groundbreaking technology that has the potential to transform patient care
- 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
Our take
Spun out from Alphabet in 2022, SandboxAQ is a company providing AI and quantum computing solutions. Using cybersecurity modules that are in line with the "third quantum revolution", SandboxAQ can migrate enterprises to a higher level of security through the use of this cutting-edge technology.
The company's approach enables cross-pollination in a range of fields, including physics, neuroscience, cryptography, and more - with products including an end-to-end crypto-agile security suite, and quantum sensing solutions. Impressively, SandboxAQ has already partnered with Deloitte and Ernst & Young (EY), as well as the US Air Force, to bring the its quantum tech to the market.
Looking forward, SandboxAQ plans to build further relationships across the public sector, to help situate the company as one of the most "battle-tested" quantum providers on the market. The company has raised significant funds that will accelerate further product development and improvements, focussing on its post-quantum cryptography software.
Steph
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
90% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Dec 2024
$300m
LATE VC
Feb 2023
$500m
GROWTH EQUITY VC
Total funding: $900m
Company benefits
- Stock options
- Unlimated vacation (PTO) and flexible work culture
- Company-wide winter and summer breaks to unwind
- Best-in-class health plans: Medical, dental and orthodontics, and vision
- Family planning and fertility benefits
- Military leave
- 100% paid parental leave
- 401k with company matching
- Education stipends
- Financial wellness resources
Company HQ
Palo Alto, CA
Articles
Leadership
Jack Hindary
(CEO)Serial entrepreneur and Co-Founder of several tech companies. Is also the author of 'Quantum Computing: An Applied Approach', one of the leading textbooks used in the field.
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