Senior Data/Machine Learning Engineer
Coca-Cola HBC
- Atlanta, Georgia, United States
- Atlanta, Georgia, United States
Über
Provide technical direction for product ML domain including problem framing, approach selection, evaluation strategy, and iteration. Define data and feature foundations: event/telemetry definitions, transformation logic, feature/label tables, and training/serving consistency. Design and maintain production ML systems: deployment patterns (batch/online), model performance/latency tradeoffs, and operational readiness. Ensure data quality, model monitoring (drift/performance), alerting, and runbooks. Set engineering standards: design reviews, code reviews, documentation, reusable ML + data workflow patterns. Mentor and empower engineers across teams. Develop, train, & evaluate models using approaches such as gradient boosting, deep learning, and ranking. Lead feature engineering, validate labels, and ensure training/serving consistency. Run experiments and evaluate models with sound methodology. Deploy & operate models in production, manage latency, reliability, and cost. Implement monitoring for data and feature freshness/quality, drift, and model performance; define alerting playbooks. Automate training and evaluation workflows, versioning, reproducibility, and artifact tracking. Participate in incident response and post‑incident reviews. Establish reusable patterns for pipelines, backfills, schema evolution, and set data governance and responsible ML standards. Partner with platform teams on data stack and MLOps tooling. Key Qualifications
6+ years experience in machine learning engineering, data engineering, or software engineering, including leading technical direction for ML/data systems. Demonstrated ownership of model development and evaluation, metric selection, error analysis, and experimentation discipline. Strong Python and SQL engineering fundamentals with production practices (testing, reviews, CI/CD). Familiarity with ML frameworks (PyTorch/TensorFlow) and data tooling (Spark, dbt, Airflow/Dagster). Experience shipping and operating production ML systems with monitoring, rollback/retraining strategies. Familiarity with data platforms, orchestration/ETL tools (Microsoft Fabric, Airflow, dbt, Spark). Preferred Qualifications
Experience building product ML systems such as personalization, recommendations, ranking, forecasting, or NLP. Experience with experimentation and measurement (A/B testing, uplift analysis, guardrails). Experience with feature pipelines or feature stores, training/serving consistency patterns. Designed and operated batch and streaming pipelines with SLAs. Experience with lakehouse/warehouse modeling, dimensional/event models, backfills, schema evolution, and data contracts. Demonstrated tech‑lead behaviors: design reviews, standards, mentoring, stakeholder alignment. Experience with model and data observability (drift detection, dashboards, alerting). Knowledge of responsible AI, data privacy (PII handling, access controls, model risk). Experience with production infrastructure (Docker/Kubernetes), workflow tooling (Airflow, Dagster) for ML jobs. Familiarity with CI/CD, testing, observability. Benefits
Pay Range: United States of America: $171,000 – $198,000 USD. Base pay varies by geography and experience. Benefits include a full range of medical, financial, and other benefits per the position. Annual Incentive Reference Value: 30% (market‑based competitive value). Travel Required: 0% – 25%. Relocation Provided: Yes. Equal Opportunity Statement
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment based on race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, disability or any other protected class. The Coca‑Cola Company will not offer sponsorship for employment status. Applicants must be authorized to work in the United States on a full‑time basis.
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Sprachkenntnisse
- English
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