Senior Machine Learning Engineer

Prestige Staffing; Sandy Springs (GA); Hybrid; USD 160,000 - 180,000; Full time

Benefits offered by this job

Competitive salary and performance bonus

401(k) with company match

Health, dental, and vision plans

Paid parental leave

Health club membership reimbursement

Mental health support subscription

Job summary

A technology staffing firm is seeking a Senior Machine Learning Engineer to join their Data Engineering team. This role involves developing deployment infrastructure for machine learning models and working collaboratively with data scientists and engineers. The ideal candidate will have strong Python development skills and cloud experience, particularly with platforms like Databricks or GCP. This position offers a competitive salary, a bonus, and a hybrid work model requiring two days in the office weekly.

Qualifications

• Strong experience in Python development for machine learning.
• Hands-on experience with cloud platforms like Databricks or GCP.
• Understanding of transitioning research code into production.

Responsibilities

• Develop and maintain infrastructure for deploying ML models.
• Collaborate with engineers to integrate ML services into applications.
• Design and implement CI/CD pipelines for machine learning models.

Skills

Python development

Cloud data science platforms (e.g., Databricks, GCP)

Infrastructure as code tools (Terraform)

CI/CD pipelines

Problem-solving skills

Agile collaboration

Tools

Terraform

Git

Job description

Summary

We are seeking a Senior Machine Learning Engineer to join our US Data Engineering team. In this role, you will work closely with data scientists and data engineers to deploy machine learning models into production, bridging the gap between model development and operational deployment. The position involves developing integrations, infrastructure, and deployment pipelines using modern cloud and automation tools in a hybrid work environment requiring two days in the office weekly.

Pay

$160,000 - $180,000 plus 10% bonus

Location

Perimeter, King and Queen / Concourse

Requirements

• Strong experience as a Python developer, particularly in machine learning engineering
• Hands‑on experience with cloud data science platforms such as Databricks or GCP
• Understanding of core data science principles and challenges of transitioning research code into production
• Proficiency with infrastructure as code tools like Terraform
• Experience with CI/CD pipelines and Git workflows
• Knowledge of API operations, monitoring, and logging
• Strong problem‑solving skills and ability to work independently
• Collaboration experience within agile teams, including roadmaps and code reviews
• Desirable: experience with additional technologies, real‑time data platforms, or an insurance background

Responsibilities

• Develop and maintain infrastructure for deploying ML models in real‑time and batch environments
• Build and maintain endpoints for serving ML models
• Collaborate with cross‑disciplinary engineers to integrate ML services into applications
• Work with platform engineers to ensure scalable, reliable deployments
• Review code contributions for quality and maintainability
• Monitor and optimize cloud‑based ML services performance
• Design and implement CI/CD pipelines for machine learning models
• Contribute to model registry development and monitoring, including tracking and upgrades

Benefits

• Competitive salary and bonus based on performance
• 401(k) with company match
• Comprehensive health, dental, vision, and FSA plans
• Company‑paid life and disability insurance
• Paid time off, including holidays, and PTO purchase options
• Paid parental leave and sabbatical after five years
• Reimbursement programs for medical travel and healthcare‑related expenses
• Health club membership reimbursement up to $600 annually
• Company‑paid Headspace subscription for mental health support
• Recognized for excellence in employee well‑being with Cigna’s 2024 Well‑Being Award
• Modern, open office environment with complimentary drinks
• Hybrid work model requiring two days per week