ML Ops Support

MOL Ops Engineer R2037 for Ford Direct ML Ops Support

(1) Job Description

• (A) Experience in Automotive and B2B areas. Designing the data pipelines and engineering infrastructure
• enterprise machine learning systems at scale
• (B) Take offline models data scientists build and deploy them into machine learning
• production system using Databricks
• (C) Identify and evaluate new technologies to improve performance, maintainability,
• and reliability of production models including new features in Databricks
• (D) Apply software engineering rigor and best practices to machine learning, including
• CI/CD, automation, etc.
• (E) Support model development, with an emphasis on auditability, versioning, and data
• security
• (F) Facilitate the development and deployment of proof-of-concept machine learning
• systems
• (G) Communicate across technical and business teams to build requirements and track
• progress
• (2) Job Qualifications for MLOPS Engineer : -
• (A) Proven experience managing machine learning models from development to
• production, including model deployment, monitoring, retraining, and scaling
• (B) Strong understanding of the machine learning lifecycle, including model versioning,
• and continuous integration/continuous delivery (CI/CD) for ML models
• (C) Expertise in cloud platforms such as AWS, GCP, or Azure for managing scalable ML
• infrastructure
• (D) Experience with containerization (Docker, Kubernetes) and orchestration of ML
• pipelines
• (E) Knowledge of infrastructure as code (Terraform, CloudFormation) and CI/CD tools
• (Jenkins, GitLab, etc.).
• (F) Solid understanding of machine learning algorithms, data preprocessing, and
• feature engineering.
• (G) Experience with ML frameworks and libraries
• (H) Strong programming skills in Python and familiarity with data engineering pipelines.

(3) Education and Experience

• (A) Bachelor’s degree from a four-year college or university in Information
• Management, Computer Science or Business Administration or a relevant area of
• study
• (B) (C) (D) (E) Data analytics or business intelligence experience (7 years).
• Model development, monitoring and production (5+ years).
• Management of analytics initiatives (3+ years).
• Experience with various data analytics tools.