Machine Learning Engineer

Responsibilities

• Collaborate with cross-functional teams—including data scientists, engineers, and architects—to build machine learning models, training tools, and simulation environments that support business functions.
• Implement the full MLOps lifecycle to deploy, operationalize, scale, and manage automated machine learning models and analytical solutions.
• Develop and test ML applications according to requirements, running targeted experiments to optimize overall system performance.
• Train and embed machine learning models into applications using programming languages (Python, Java, R) and core libraries (TensorFlow, Keras, Scikit-learn).
• Explore and visualize data to uncover key insights and identify specific factors that impact model accuracy and performance.
• Manage and deploy cloud-based ML services across major cloud computing environments, including AWS, Azure, or Google Cloud Platform (GCP).
• Follow Agile methodologies to deliver production-ready, highly testable code in small, efficient, and continuous iterations.

Requirements

• Master’s degree in Applied Mathematics, Statistics, Computer Science, or related fields.
• Verifiable work experience defining and implementing data pipelines and machine learning algorithms.
• Proficiency in Agile Development and Git Operations.
• Experience creating, maintaining, and communicating complex technical documentation for machine learning systems.

Qualifications

• Experience with the Sponsor’s primary cyber risk and compliance automation tools.

Skills

• Strong technical background and knowledge in machine learning.
• Collaborative skills with cross-functional teams.
• Experience with cloud computing environments (AWS, Azure, GCP).
• Ability to communicate complex technical information effectively.

Benefits

• Competitive salary commensurate with experience.
• Flexible working hours.
• Professional development opportunities.

Pay

• Commensurate with experience.

Schedule

• Full-time.

Benefits

• Health insurance.
• Retirement plan.
• Employee assistance program.

Skills

• Programming languages (Python, Java, R).
• Core libraries (TensorFlow, Keras, Scikit-learn).
• Data visualization tools.
• Cloud computing platforms (AWS, Azure, GCP).
• Agile development methodologies.

Physical Requirements

• Must be able to remain in a stationary position 50% of the time.
• Frequent communication with co-workers, management, and customers.