Machine Learning Engineer

Company Overview

[Company information is not provided.]

Job Summary

The Machine Learning Engineer will be responsible for developing and deploying machine learning models, leveraging cloud services and MLOps practices to enhance the overall efficiency of AI-driven projects. This role is essential for building robust ML applications that meet the organization’s technological needs.

Responsibilities

• Understand and apply basic machine learning concepts, including core ML algorithms and evaluation metrics.
• Perform hands-on training and testing of small-scale machine learning models.
• Utilize Python programming skills, particularly with libraries like pandas, NumPy, matplotlib, and scikit-learn for AI and ML projects.
• Work with GCP services, specifically Vertex AI Services, BigQuery, Cloud Storage, and Cloud Run.
• Implement MLOps practices, including version control using GitHub and understanding CI/CD pipelines tailored for AI and ML.
• Write Infrastructure as Code (IaC) using Terraform templates for medium complexity applications involving multiple GCP components.

Qualifications

• Proficiency in basic machine learning concepts with practical experience.
• Strong Python programming skills, with familiarity in libraries relevant for data manipulation and visualization.
• Mid-level experience with GCP services, particularly Vertex AI and BigQuery.
• Knowledge of MLOps practices, specifically CI/CD principles for machine learning applications.
• Experience in Infrastructure as Code (IaC) using Terraform.
• Familiarity with Docker.
• Understanding of observability in machine learning, including GCP prompt/response observability services and possibly experience with Arize Observability.

Preferred Skills

• Demonstrated expertise in observability or evaluation metrics within machine learning contexts is a plus.

Experience

• Specific experience requirements are not detailed. Candidates should possess the necessary technical skills and some relevant project experience.

Environment

• The typical work setting and location for this role have not been specified.

Salary

• Salary information is not provided.

Growth Opportunities

• Advancement opportunities within the company are not specified.

Benefits

• Benefits are not detailed.