Senior ML Engineer — Production Pipelines on Databricks

Xforia Global Talent & Technology Solutions; United States; Vor Ort; USD 140.000 - 190.000; Vollzeit

Zusammenfassung

Xforia Global Talent & Technology Solutions seeks a Senior Data Scientist to join a centralized ML team in the United States. You will own productionizing ML models and pipelines end-to-end, collaborating across data science, engineering, and product to deliver production-ready solutions that impact revenue.

The role emphasizes deployment, monitoring, and optimization on cloud platforms such as Databricks and Azure, with strong Python coding and production-grade practices required.

Qualifikationen

• 3+ years of professional experience in a technical environment.
• Strong Python expertise with production-grade coding, modularization, testing, and performance tuning.
• Hands-on ML pipeline experience including deployment, orchestration, monitoring, and optimization.
• Solid knowledge of statistical and machine learning techniques.
• Experience with data extraction, cleaning, and analysis.
• Excellent verbal and written communication skills.

Aufgaben

• Take ownership of productionizing ML pipelines, including refactoring and optimizing for performance.
• Design, build, deploy, and monitor ML models in a production environment.
• Collaborate with data scientists and engineers to embed ML solutions in business apps.
• Improve and maintain existing codebases with quality, modularity, and testing.
• Partner with stakeholders to translate business needs into scalable ML solutions.
• Communicate complex results to technical and non-technical audiences.

Kenntnisse

Python

ML pipelines

Statistics

Data extraction

Communication

SQL

Databricks

Spark

CI/CD

Model monitoring

Azure

AWS

GCP

Tableau

Power BI

Tools

MLflow

CI/CD

Databricks

Spark

Jobbeschreibung

Xforia Global Talent & Technology Solutions seeks a Senior Data Scientist to join a centralized ML team in the United States. You will own productionizing ML models and pipelines end-to-end, collaborating across data science, engineering, and product to deliver production-ready solutions that impact revenue.

The role emphasizes deployment, monitoring, and optimization on cloud platforms such as Databricks and Azure, with strong Python coding and production-grade practices required.