Machine Learning Engineer, Data Acquisition - Remote

Overview

As a Machine Learning Engineer at Zus, you will leverage your expertise in machine learning and MLOps to enhance healthcare data interoperability through innovative solutions and robust data pipelines.

In Short

• Work on a shared health data platform to improve healthcare data interoperability.
• Develop, deploy, and optimize machine learning solutions.
• Collaborate with cross-functional teams to innovate data collection and normalization techniques.
• Conduct research to explore new methodologies in machine learning.
• Build and maintain robust data pipelines in collaboration with data engineers.
• Implement MLOps practices for model deployment and maintenance.
• Stay updated with advancements in machine learning and AI.
• Present findings and educate team members on new techniques.
• Utilize programming languages such as Python, Java, or Go.
• Engage with stakeholders to deliver high-quality solutions.

Requirements

• 3+ years of experience in machine learning and MLOps.
• Proficiency in Python, Java, or Go.
• Strong understanding of machine learning frameworks like TensorFlow and PyTorch.
• Experience with MLOps tools and cloud services (AWS, GCP, Azure).
• Excellent analytical skills and attention to detail.
• Strong communication skills for explaining technical concepts.
• Ability to work effectively in a team environment.

Benefits

• Opportunity to work in a pioneering healthcare tech startup.
• Collaborative and innovative work environment.
• Engagement in impactful projects that enhance patient care.
• Continuous learning and professional development opportunities.
• Flexible work arrangements.