Machine Learning Engineer

CLA (CliftonLarsonAllen)•Akron, OH

About The Position

CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you. CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other. CLA is growing and seeking to hire an experienced Machine Learning Operation Engineer: 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. This is an opportunity to learn, build, and grow alongside experienced developers in a supportive, collaborative environment. How you’ll create opportunities in this role: •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. •Assist with ensuring the security and scalability of the MLOps infrastructure to handle large volumes of data and models. •Support maintenance of documentation for MLOps processes and systems. •Collaborate with cross-functional teams to understand business needs and translate them into technical requirements. •Ensure compliance with data security and privacy regulations. •Stay 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.
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.

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.
Assist with ensuring the security and scalability of the MLOps infrastructure to handle large volumes of data and models.
Support maintenance of documentation for MLOps processes and systems.
Collaborate with cross-functional teams to understand business needs and translate them into technical requirements.
Ensure compliance with data security and privacy regulations.
Stay up to date with industry trends and advancements in machine learning and MLOps.