Description: We're working closely with a consulting firm in the healthcare industry to identify a Machine Learning Engineer. This individual will be working closely with the team to build machine learning algorithms for massive data sets. This Machine Learning Engineer will be asked to build and enhance platforms and implement Machine Learning Ops while consistently providing research while evaluating the latest architecture patterns and technologies through learning and proof of concepts and prototype solutions.
Responsibilities:
Build, orchestrate, and monitor model pipelines.
Scale ML algorithms for large datasets and strict SLAs.
Enhance ML engineering platforms and components.
Implement ML Ops for model KPI tracking, data/model drift, and feedback loops.
Write production-ready, testable code.
Ensure high-quality deliverables through best practices and reviews.
Collaborate with client and global teams.
Use tools like bug tracking, code review, and version control.
Qualifications:
Bachelor's or Master's in Computer Science or related field.
2-4 years of experience in deploying and productionizing ML models.
Strong programming skills in Python/PySpark.
Experience with ML platforms (e.g., Dataiku, Sagemaker, MLFlow).
Experience deploying models to cloud services (AWS, Azure, GCP).
Expertise in high-performance, scalable ML models.
Experience with feature engineering and real-time model predictions.
Proficiency in ML Ops for performance tracking.
Solid understanding of machine learning and deep learning fundamentals.
Knowledge of data structures, algorithms and design patterns.
Experience with Spark or other distributed computing frameworks.
Understanding of DevOps, CI/CD, data security, and cloud platform design.
Experience in data engineering for big data systems.
Contact: kkerr@judge.com
This job and many more are available through The Judge Group. Find us on the web at www.judge.com
