MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
About the role
- Machine Learning Engineer designing scalable AI/ML services and pipelines in a cloud-based environment. Collaborate on cutting-edge R&D initiatives with a global team.
Responsibilities
- Design, develop, and architect high-performance AI/ML services and pipelines in a cloud-based environment.
- Contribute to cutting-edge R&D initiatives, including service integration with emerging frameworks and platforms.
- Assist with the technical resolution of issues on mission-critical production systems, embracing the philosophy: "you build it, you own it, you run it."
- Think outside the box to devise solutions that scale, are fault-tolerant, easy to grasp, and elegant.
Requirements
- 3+ years of hands-on experience with Python.
- 4+ years of hands-on experience with machine learning, deep learning, large language models, and/or foundational models.
- Hands-on experience with cloud-based architectures/infrastructures (AWS), specifically related to AI/ML pipelines.
- Experience in building workflows for automated data preparation, curation, and annotation, including secure, scalable storage and retrieval for model training.
- Experience in fine-tuning models, training, validating, testing, and deploying them in production settings.
- Experience in vision-based AI, including automated data labeling, object detection, and image segmentation.
Benefits
- Your growth is our growth. We invest in your future with paid training and other professional opportunities.
- Recognition and reward. We acknowledge diligence and hard work through annual pay increases for good performance.
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Degree requirement
No Education Requirement
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