ML Engineer - ML Ops & Data Pipelines (Flexible Hours)

Makpar; United States; A distancia; USD 120.000 - 180.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible work schedules

Career development opportunities

Competitive compensation package

Descripción de la vacante

Makpar is seeking an ML Engineer to join our team supporting Federal government projects. You will develop, train, and optimize machine learning models, working closely with data engineers and developers to prepare data, evaluate models, and deploy scalable solutions.

Responsibilities include designing data pipelines, integrating ML capabilities, and enabling production readiness across environments. You will mentor peers, participate in code reviews, and help drive CI/CD improvements within

Formación

• Proficiency in Python and ML libraries (scikit-learn, pandas, NumPy).
• Experience with Databricks for data processing and ML workflows.
• Understanding REST APIs and data pipelines integration.

Responsabilidades

• Develop, train, and optimize ML models for predictive analytics and decision-making.
• Collaborate with data engineers and developers to prepare data and deploy models.
• Lead CI/CD improvements and provide technical guidance to Agile teams.
• Document architecture, experiments, and deployment steps.

Conocimientos

Python

scikit-learn

Pandas

NumPy

Databricks

REST APIs

Git/GitHub

CI/CD

ML deployment

Agile

Educación

Bachelor's degree in Computer Science / Data Science / ML

Herramientas

Git

GitHub

Jira

Confluence

Descripción del empleo

Makpar is seeking an ML Engineer to join our team supporting Federal government projects. You will develop, train, and optimize machine learning models, working closely with data engineers and developers to prepare data, evaluate models, and deploy scalable solutions.

Responsibilities include designing data pipelines, integrating ML capabilities, and enabling production readiness across environments. You will mentor peers, participate in code reviews, and help drive CI/CD improvements within