Senior Machine Learning Engineer

Cincinnati Children's

3d•Remote

About The Position

This role focuses on the analysis and development of machine learning (ML) standards, processes, and best practices. The Senior Machine Learning Engineer will collaborate with stakeholders to identify and plan for enterprise ML portfolio needs, guide ML team members, and translate complex requirements into well-scoped ML projects. The engineer will develop and ensure the scalability of ML applications, work closely with data scientists and data engineers, create performance evaluation metrics, and extend existing ML libraries and frameworks. The position requires strong technical and business skills, including proficiency in various ML models, probability and statistical models, advanced programming in Python, C/C++, R, and Java, and experience with numerical and data science libraries. Familiarity with major ML frameworks, web technologies, DevOps/MLOps, data structures, and software architecture is also necessary. The role demands a strong understanding of probability, statistics, and algorithms, the ability to conduct scientific experiments and analyze results, and excellent communication skills to convey technical concepts to both technical and business audiences. Collaboration across multiple teams, including analytics, development, product management, and operations, is crucial. The engineer will also stay abreast of AI/ML trends and identify action plans for CCHMC. Project execution and management involve executing tasks with urgency and quality, communicating status effectively, following project management requirements, and serving as a technical lead for moderately complex projects, collaborating with project managers on scope, risk, and budget. Leading project meetings and workgroups is also part of the responsibilities.

Requirements

Proficiency in machine learning models for classifications, decision trees, support vector machines and deep learning.
Strong understanding of probability and statistical models (generative and descriptive models).
Advanced programming skills with Python C/C++, R, Java.
Experience with numerical and data science libraries (scikit-learn, Pandas, NumPy, kernlab, etc.).
Experience with at least one major machine learning framework (TensorFlow, PyTorch, etc.).
Knowledge of web technologies, such as HTML, CSS and JavaScript.
Experience in DevOps/MLOps.
Understanding of data structures, data modeling and software architecture.
Strong Knowledge of probability, statistics, and algorithms.
Bachelor's degree in computer science, statistics, economics or related fields
5+ years of work experience in a related job discipline

Nice To Haves

Experience in other IT roles or functions such as quality assurance/testing, development, enterprise architecture, or project management.
Demonstrated the ability to manage large data science projects and various teams
3+ yrs of relevant project exp. in successfully launching, planning, executing ML projects
Experience working on a project using Agile or iterative methods
Specialization in ML, AI, cognitive science or data science
A specialization in text analytics, image recognition, graph analysis OR other specialized ML techniques such as deep learning, etc

Responsibilities

Implement ML standards, processes and best practices.
Collaborate with stakeholders to identify and plan for enterprise ML portfolio needs.
Guide ML team members on their deliverables and activities.
Translate complex requirements into well-scoped machine learning projects.
Develop machine learning applications according to requirements.
Ensure machine learning solutions are scalable to meet enterprise requirements.
Work closely with data scientists and data engineers to guide development of machine learning models.
Create metrics to continuously evaluate the performance of machine learning solutions.
Extend existing machine learning libraries and frameworks as needed.
Run experiments scientifically and analyze results using machine learning models.
Effectively communicate technical concepts and results to technical and business audiences in a comprehensive manner.
Collaborate effectively across multiple teams and stakeholders, including analytics teams, development teams, product management and operations.
Stay abreast of trends in AI/ML and identify action plan for CCHMC.
Execute own project tasks with urgency and to a high level of quality.
Communicate status clearly and effectively using departmental project management tools.
Follow time-tracking and other project management requirements.
Participate actively in project meetings, stand-ups, etc.
Serve as technical lead for moderately complex projects, collaborating with project managers to ensure project scope/risk/budget/etc. are adequately managed.
Lead project meetings and workgroups.