High-Performance Data Architect
1 week ago
About Altis Labs
Altis Labs is a leading-edge AI company accelerating clinical trials with innovative imaging solutions. We're on a mission to bring life-saving treatments to patients sooner by bridging the gap between AI and human expertise.
The Challenge
Current imaging interpretation methods like RECIST 1.1 often fall short, resulting in suboptimal drug development. Top biopharma sponsors rely on our AI models to measure treatment effect with greater confidence, optimizing trial design and accelerating novel treatments.
About the Position
We're seeking an exceptional Senior Data Engineer to join our team and play a pivotal role in shaping our data infrastructure. As a seasoned expert, you'll design and implement scalable data services that empower machine learning applications, leveraging petabytes of medical imaging data and associated clinical data.
Your Responsibilities:
- Build and maintain a high-performance data service for AI model training and deployment
- Collaborate closely with ML scientists, software engineers, and clinicians to drive innovation
- Present your work to stakeholders and at industry conferences
What You Need:
- 5+ years of experience building scalable data services for ML applications
- Proven expertise in ETL processes, data modeling, and data warehousing
- Strong programming skills in languages like Python and C++
- Familiarity with cloud-based frameworks, including AWS, GCP, or Azure
- Experience with Git and distributed computing
- Excellent communication skills in English
Preferred Qualifications:
- Experience in the medical domain, including DICOM and other imaging modalities
- Knowledge of Kubernetes, Kubeflow, or MLOps tools
- Experience building deep learning models on 3D data
Why Join Us?
Competitive pay and generous equity participation
Coverage for medical, vision, and dental insurance
4 weeks of vacation per year
Flexible work organization and remote work options
Estimated Salary: $140,000 - $160,000 per annum, based on industry standards and location considerations.
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