Senior Data/Machine Learning Engineer (AI)

Location: Atlanta, Georgia, United States. Full-time onsite role with 0–25% travel. Relocation is provided. Applicants must be currently authorized to work full-time in the United States; visa sponsorship is not available.

Salary: $171,000–$198,000 annual base pay, plus a 30% annual incentive reference value.

Company

A global beverage company building digital products and platforms that support customer journeys, service delivery, sales workflows, and consumer experiences across North America.

What you will do

• Lead technical direction for product machine learning domains, including problem framing, approach selection, evaluation, and iteration.
• Build ML-powered data products for transaction modeling, recommendations, ranking, forecasting, and optimized actions across retail, foodservice, and digital channels.
• Develop scalable data preparation, feature engineering, training, and inference pipelines for batch and near-real-time use cases.
• Deploy and operate production models, APIs, and services with attention to latency, reliability, cost, monitoring, rollback, and retraining.
• Establish reusable engineering standards for data quality, observability, model governance, responsible ML, and data privacy.
• Partner with Product, Design, Data Science, Analytics, and platform teams while mentoring engineers and driving design reviews.

Requirements

• 6+ years of experience in machine learning engineering, data engineering, or software engineering, including technical leadership for ML or data systems.
• Strong Python and SQL skills with production practices including testing, code reviews, and CI/CD.
• Experience developing, evaluating, deploying, and operating machine learning systems in production.
• Knowledge of supervised learning, evaluation metrics, experimentation, error analysis, bias, leakage, and model failure modes.
• Experience with data platforms, warehouses or lakehouses, orchestration, ETL, feature pipelines, and MLOps practices.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice to have

• Experience with PyTorch, TensorFlow, Spark, dbt, Airflow, Dagster, Microsoft Fabric, Docker, Kubernetes, or feature stores.
• Experience with personalization, recommendations, ranking, forecasting, NLP, deep learning, transformers, computer vision, or RAG.
• Experience with A/B testing, uplift analysis, model and data observability, responsible AI, PII handling, and access controls.

Culture & Benefits

• Cross-functional teams are empowered to solve problems and accountable for measurable outcomes.
• Collaboration spans discovery through delivery, with continuous learning based on data and customer insight.
• Benefits include medical, financial, and other position-dependent benefits.
• The role emphasizes inclusive, curious, empowered, and agile ways of working.