Machine Learning Engineer(W2 only)

Position: Senior Machine Learning Engineer

Location: Las Vegas, Nevada (hybrid 3days to office) Possible to convert into fulltime

Essential Duties & Responsibilities

• Architect and build scalable cloud‑based data and ML pipelines, as well as a robust ML framework to support model training, deployment, inference, and monitoring at scale.
• Lead the design, development, evaluation, validation, and implementation of machine learning models aligned to business objectives.
• Conduct data preprocessing, feature engineering, exploratory data analysis, and deep dives to uncover trends and support model development and business insights.
• Manage and optimize end‑to‑end ML workflows, including data ingestion, orchestration, and pipeline reliability.
• Implement comprehensive model monitoring, including performance tracking, drift detection, data quality checks, and automated retraining triggers.
• Design and implement predictive analytics solutions, experiments, and model algorithms to improve forecasting, optimization, and operational decision‑making.
• Incorporate clear and effective data visualization techniques for both technical and non‑technical audiences.
• Make informed infrastructure and modeling decisions, including model selection, feature strategies, hyperparameter tuning, and evaluation methodologies.
• Develop and maintain detailed documentation for operational readiness and cross‑team alignment.
• Ensure code quality, security, and compliance; maintain ML governance best practices, including Responsible and Explainable AI standards.
• Lead code reviews and provide technical guidance, mentorship, and best‑practice reinforcement across the team.
• Stay current with industry trends, emerging research, and new technologies to drive continuous improvement and innovation in ML engineering.

Minimum Qualifications

• 21 years of age.
• Proof of authorization to work in the United States.
• Bachelor’s degree in computer science, engineering, data science, statistics, mathematics, or a related field (Master’s preferred).
• Ability to obtain and maintain Nevada Gaming Control Board registration and other required certifications.
• Minimum of 5+ years of relevant ML engineering experience.
• Hands‑on experience building, scaling, and deploying ML pipelines in Python, preferably within Google Cloud Platform and Databricks.
• Strong programming and data manipulation skills (Python, SQL, Spark, Pandas), with experience in machine learning frameworks (TensorFlow, PyTorch, scikit‑learn) and optimization tools.
• Experience with CI/CD, Git, and automated ML deployment workflows.
• Demonstrated experience in statistical/quantitative analysis, forecasting, predictive modeling, anomaly detection, experimentation, and optimization algorithms.
• Expertise designing and developing ML systems, including distributed computing architectures (Spark, Delta Lake, Kubernetes).
• Familiarity with MLflow, feature stores, model registries, and lineage tooling.
• Experience implementing robust model monitoring, including performance tracking, drift detection, and automated retraining.
• Experience with A/B testing frameworks, online evaluation, and model rollout strategies.
• Experience designing ML governance workflows in regulated environments.
• Strong understanding of ML fundamentals, ability to translate business requirements into scalable ML solutions, and experience in hyperparameter optimization and experiment tracking.
• Ability to work with modern ML techniques, including foundation models, embeddings, vector databases, retrieval‑augmented ML approaches, and generative AI where relevant.
• Strong understanding of time‑series forecasting, demand prediction, and optimization algorithms.
• Excellent analytical, problem‑solving, communication, and cross‑functional collaboration skills.
• Ability to explain complex technical concepts in clear, simple terms for diverse business audiences.

Physical Requirements

Must be able to

• Physically access all areas of the property and drive areas with or without reasonable accommodation.
• Maintain composure under pressure and consistently meet deadlines with internal and external customers and contacts.
• Ability to interact appropriately and effectively with guests, management, other team members, and outside contacts.
• Ability for prolonged periods of time to walk, stand, stretch, bend and kneel.
• Work in a fast-paced and busy environment.
• Work indoors and be exposed to various environmental factors such as, but not limited to, CRT, noise, dust, and cigarette smoke.