Senior ML Engineer - CG

Role: Senior ML Engineer
Duration: 12 Months Location: Atlanta GA (Fully onsite)

Job Description:

• ML Models Hosting Technical Architecture:
• Design and implement data storage solutions using ADLS and other relevant technologies.
• Develop and maintain model training environments using Databricks and other platforms.
• Optimize model run-time and latency for on-demand workloads.
• Create and manage API layers for model serving.
• Ensure robust security architecture for ML models and data.
• Creation, Training, and Serving of ML Models:
• Develop and deploy ML models using Databricks notebooks and GitLab for version control.
• Implement batch processing solutions using Databricks and other tools.
• Deploy models for real-time inference in on-demand environments.
• Collaborate with data engineers and data scientists to integrate models into production systems.
• Collaboration and Communication:
• Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Document processes, models, and code to ensure knowledge sharing and maintainability.
• Stay updated with the latest industry trends and technologies in machine learning and data engineering.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in ML engineering, including model creation, training, and serving.
• Strong knowledge of Databricks, Unity Catalog, ADLS, and Databricks notebooks.
• Proficiency in using GitLab for version control.
• Experience with API development and deployment.
• Understanding of security best practices for ML models and data.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Experience with cloud platforms such as Azure
• Familiarity with big data processing tools like Apache Spark.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Platform management, SQL, cloud artificial intelligence, computer science, machine learning, science & research

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Role: Senior ML Engineer
Duration: 12 Months Location: Atlanta GA (Fully onsite)

Job Description:

• ML Models Hosting Technical Architecture:
• Design and implement data storage solutions using ADLS and other relevant technologies.
• Develop and maintain model training environments using Databricks and other platforms.
• Optimize model run-time and latency for on-demand workloads.
• Create and manage API layers for model serving.
• Ensure robust security architecture for ML models and data.
• Creation, Training, and Serving of ML Models:
• Develop and deploy ML models using Databricks notebooks and GitLab for version control.
• Implement batch processing solutions using Databricks and other tools.
• Deploy models for real-time inference in on-demand environments.
• Collaborate with data engineers and data scientists to integrate models into production systems.
• Collaboration and Communication:
• Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Document processes, models, and code to ensure knowledge sharing and maintainability.
• Stay updated with the latest industry trends and technologies in machine learning and data engineering.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience in ML engineering, including model creation, training, and serving.
• Strong knowledge of Databricks, Unity Catalog, ADLS, and Databricks notebooks.
• Proficiency in using GitLab for version control.
• Experience with API development and deployment.
• Understanding of security best practices for ML models and data.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Experience with cloud platforms such as Azure
• Familiarity with big data processing tools like Apache Spark.
• Knowledge of containerization and orchestration tools like Docker and Kubernetes.
• Platform management, SQL, cloud artificial intelligence, computer science, machine learning, science & research

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.