Machine Learning Engineer

Brooksource; Cincinnati (OH); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Health benefits

HSA

401(k) with match

PTO

Paid holidays

Employee Assistance Program

Job summary

Brooksource seeks a Senior Machine Learning Engineer for the Data Science Enablement squad to deploy a secure, automated pipeline and to educate data scientists on MLOps. You will balance engineering tasks with change management and training, ensuring robust, scalable workflows.

As the deployment framework matures, you will enable MLFlow, A/B testing, real-time endpoints, and further automation with Model Risk Management (MRM) to meet regulatory standards.

Qualifications

• 3–5+ years of experience in machine learning and MLOps.
• Experience with AWS SageMaker and end-to-end ML models.
• Data integration and management using IBM DB2 and Snowflake.
• Strong CI/CD and automation.
• Programming in Python, R, SQL and/or Java.
• Experience with Jira, Terraform, GitHub, Jenkins.
• Knowledge of Docker and Kubernetes.

Responsibilities

• Develop and implement a secure, automated deployment pipeline.
• Educate and mentor team members on MLOps practices.
• Balance engineering tasks with change management and training.
• Enhance MLOps capabilities with advanced tools and techniques.

Skills

Machine Learning

MLOps

Python

SQL

Tools

AWS SageMaker

Jira

Terraform

GitHub

Jenkins

Docker

Kubernetes

Job description

Join our Data Science Enablement squad as a Senior Machine Learning Engineer. You will use an existing batch inference model to establish a secure, automated deployment pipeline. This role involves both engineering and change management, including architecture and training, with a focus on educating data scientists and other Data Science Enablement members on MLOps. Once the foundational deployment framework is in place, you will enable additional MLOps capabilities such as MLFlow, A/B testing, real-time endpoints, and further automation with Model Risk Management (MRM).

Key Responsibilities:

• Develop and implement a secure, automated deployment pipeline.
• Educate and mentor team members on MLOps practices.
• Balance engineering tasks with change management and training.
• Enhance MLOps capabilities with advanced tools and techniques.

Preferred Experience:

• Experience in highly regulated industries like banking, finance, or healthcare.

Qualifications:

• Minimum of 3-5+ years of experience in machine learning and MLOps.
• Proven experience with AWS Sagemaker and building end-to-end machine learning models.
• Experience with data integration and management using IBM DB2 and Snowflake (or like databases)
• Strong understanding of CI/CD pipelines and automation tools.
• Proficiency in programming languages such as Python, R, SQL and/or Java.
• Use of standard DevOps tools such as Jira, Terraform, GitHub, Jenkins
• Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).

EEO Statement:

Brooksource is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, physical or mental disability, protected medical condition as defined by applicable state or local law, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances.

Benefits & Perks:

Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

Pay Disclaimer:

The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.