Machine Learning Operations Engineer II

About the role

This position offers growth, flexibility and a collaborative work environment. We're looking for a motivated and curious Machine Learning Operation Engineer to join our Data Science Team.

Responsibilities

• Assist with design and development of MLOps infrastructure to support the deployment, management, and monitoring of machine learning models within the firm.
• Collaborate with data scientists and engineers to ensure seamless integration of data science and engineering processes.
• Support maintenance of automated workflows and pipelines for efficient model deployment and monitoring.
• Troubleshoot and resolve any issues with model performance, data pipelines, or infrastructure.
• Affiliate with ensuring the security and scalability of the MLOps infrastructure to handle large volumes of data and models.
• Affiliate with maintenance of documentation for MLOps processes and systems.
• Affiliate with collaboration with cross-functional teams to understand business needs and translate them into technical requirements.
• Affiliate with ensuring compliance with data security and privacy regulations.
• Affiliate with staying up to date with industry trends and advancements in machine learning and MLOps.

Requirements

• 2+ years' experience as a Data/ML Engineer
• Bachelor's degree is required. Combination of relevant experience, education, and training may be accepted in lieu of degree.

Qualifications

• Familiarity with cloud platforms (e.g., AWS, Azure, GCP).
• Basic understanding of SQL and experience with ETL pipeline design and maintenance.
• Knowledge of CI/CD concepts and experience with tools like Jenkins, Git, Perforce, etc.
• Proficiency in programming languages such as Python.
• Knowledge of data pipeline architecture and data transformation.
• Knowledge of machine learning model deployment and management.
• Familiarity with performance monitoring and optimization techniques.
• Basic understanding of machine learning and DevOps principles.

Skills

• Cloud Platforms (AWS, Azure, GCP)
• SQL
• ETL Pipeline Design
• CI/CD Concepts
• Programming Languages (Python)
• Data Pipeline Architecture
• Machine Learning Model Deployment
• Performance Monitoring
• Machine Learning Principles
• DevOps Principles

Benefits

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Pay

Details TBD.

Schedule

Details TBD.

Benefits

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