ML Platform Engineer (Staff/Senior)

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Job Overview

Abridge is seeking a highly skilled Machine Learning (ML) Platform Engineer at the Staff or Senior level to join our dynamic team. In this role, you will be responsible for designing, developing, and optimizing our ML platforms to enhance our core services. You will collaborate with cross-functional teams to ensure seamless integration and deployment of machine learning models, facilitating data-driven decision-making across the organization. Your expertise will be critical in creating scalable and efficient solutions that leverage advanced machine learning techniques, ultimately contributing to the enhancement of our healthcare technology offerings.

Job Responsibilities

• Design, implement, and maintain the infrastructure and tools for scalable machine learning applications.
• Collaborate with data scientists and software engineers to integrate machine learning models into production systems.
• Optimize the performance of existing machine learning models and contribute to model evaluation and retraining processes.
• Develop comprehensive documentation and guidelines for machine learning best practices and deployment strategies.
• Monitor and troubleshoot production-level machine learning systems to ensure operational efficiency and reliability.
• Conduct research and stay updated on evolving technologies and methodologies in the field of machine learning.
• Mentor junior engineers in machine learning best practices and foster a culture of knowledge sharing.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 5+ years of experience in software engineering with a focus on machine learning platforms.
• Proficiency in programming languages such as Python, Java, or Scala.
• Extensive experience with ML frameworks such as TensorFlow, PyTorch, or similar.
• Experience using containerization technologies like Docker and orchestration platforms such as Kubernetes.
• Strong understanding of data pipelines, ETL processes, and database management.
• Excellent problem-solving skills with the ability to work independently and in a team environment.

Technologies & Tools

The ideal candidate will work with a diverse array of technologies and tools, including cloud platforms like AWS, GCP, or Azure, machine learning libraries such as scikit-learn and XGBoost, as well as version control systems like Git. Familiarity with data visualization tools and experience with CI/CD pipelines will be advantageous in this role.

Ideal Candidates

Ideal candidates will exhibit a strong passion for machine learning and its applications in the healthcare sector. They will be innovative thinkers who are motivated by solving complex problems and are committed to best practices in software engineering. The ability to collaborate effectively within teams, as well as independently, is essential. Candidates should possess excellent communication skills with a knack for simplifying technical concepts for stakeholders across various levels of expertise.