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AI Machine Learning Engineer
Posted: 09/12/2026
Job Number: MWFzbHhLQnRPbm5PbXczYWtrMC95Zz09
Pay Rate: 60-65 Hourly USD
Job Description
- Title: AI Machine Learning Engineer
- Location: Alpharetta, GA
- Duration: Contract
- Pay Range: DOE
- Experience: 7–12 Years
We welcome candidates with all U.S. work authorization types, provided they are legally authorized to work in the United States.
Key Responsibilities
- Build and manage end-to-end Machine Learning lifecycles using Vertex AI, including feature engineering, model training, and deployment of scalable prediction endpoints.
- Develop and optimize ML solutions using Python, Pandas, Scikit-learn, TensorFlow, and PyTorch.
- Design and implement high-performance ETL/ELT pipelines using Python and Java to ingest and process massive datasets.
- Create unified semantic layers to ensure AI-generated insights and raw data are accurately represented in business dashboards.
- Maintain and optimize BigQuery data warehouses, focusing on performance tuning, partitioning, and cost efficiency.
- Utilize Dataflow and Apache Beam for real-time data processing and complex event-driven architectures.
- Implement event-driven data processing using Pub/Sub.
- Partner with AI teams to operationalize ML models and support MLOps practices.
- Collaborate with Business Analysts to translate complex data into Looker visualizations.
- Support end-to-end AI/ML orchestration and productionization of machine learning solutions.
- 7–12 years of relevant professional experience.
- Strong Python development experience.
- Strong Machine Learning and AI/ML orchestration experience.
- Hands-on experience with Vertex AI and end-to-end ML lifecycle management.
- Experience with Pandas and Scikit-learn.
- Experience with deep learning frameworks such as TensorFlow and PyTorch.
- Experience designing and implementing high-performance ETL/ELT pipelines.
- Strong experience with BigQuery data warehouses.
- Experience with Dataflow / Apache Beam for real-time data processing.
- Experience with Pub/Sub and event-driven architectures.
- Experience with MLOps and operationalizing machine learning models.
- Strong data processing, model deployment, and performance optimization skills.
- Experience with Java for data engineering and ETL/ELT pipelines.
- Experience creating unified semantic layers for analytics and AI-generated insights.
- Experience with BigQuery partitioning and cost optimization.
- Experience translating complex datasets into Looker dashboards and visualizations.
- Experience collaborating with AI teams, MLOps teams, and Business Analysts.
- Experience with GenAI / LLMOps and AIOps environments.
- Experience with Deep Learning – AIOps and Machine Learning – AIOps.
We are committed to fostering an inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by applicable law.