Find Jobs
Find Jobs Near You – Available Work in Your Location
AI/ML Engineer
Career Insights for Machine Learning Engineer
See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.
Scorecard
Based on Georgia data
Review key factors to help you decide if this role fits your goals. How is this calculated?
What they do
A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
$121,322 / year median in Georgia
Job Description
AI/ML Engineer (Vinings, GA, 30339) | 09/04/26 Easy Apply Job Description Overview The AI/ML Engineer is responsible for designing, developing, and deploying scalable artificial intelligence and machine‑learning solutions that enhance customer interactions, automate decision-making, and improve operational efficiency. This role involves building intelligent workflows, predictive models, data‑driven insights, and automation frameworks in collaboration with cross‑functional engineering, product, and support teams. Responsibilities AI‑Driven Interactions & Automation Design and implement AI‑powered conversational flows and automated decisioning logic.
Build secure data integrations to enable real‑time processing and intelligent responses.
Optimize large language model (LLM) workflows for accuracy, performance, and usability. Data Analytics & Predictive Modeling Apply machine learning techniques to structured and unstructured data from various systems.
Develop predictive models to identify trends, detect anomalies, and support proactive decision‑making.
Implement monitoring and alerting mechanisms to ensure timely detection and escalation of issues. Real‑Time Intelligence for Internal Teams Integrate AI‑driven insights into internal tools to support agents and operations teams.
Deliver real‑time recommendations, next‑best‑actions, and contextual guidance based on combined system and interaction data.
Enhance employee productivity through intelligent assistance and dynamic knowledge retrieval. Automated Workflows & Operational Safety Build diagnostic and remediation automation with appropriate safety, governance, and auditability controls.
Ensure all automated actions adhere to defined compliance, authorization, and security rules.
Develop dashboards and reporting tools for system health, workflow performance, and model metrics. Qualifications
JOB REQUIREMENTS
Minimum Qualifications 3+ years of experience in AI/ML engineering, data science, or intelligent automation.
3+ years of hands‑on experience with modern cloud platforms including compute, data, and AI services.
3+ years of proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or scikit‑learn.
Experience building real‑time, streaming, or event‑driven data pipelines.
Proven track record of designing, deploying, and maintaining production‑grade ML systems.
Knowledge of APIs, microservices, and secure integration patterns. Preferred Qualifications 3+ years of Experience with IoT, device telemetry, or distributed sensor data systems.
3+ years of Background in LLM tuning, retrieval‑augmented generation (RAG), and conversational AI.
Familiarity with contact center platforms or enterprise workflow automation systems.
Understanding of authentication, authorization, and access‑control frameworks.
PHYSICAL DEMANDS
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the position.