Machine Learning Engineer

Wynn Al Marjan Island

About the Position:

Wynn Al Marjan Island is currently seeking a Machine Learning Engineer to join the resort s Information Technology team.

The primary duties and responsibilities of this role are:

• Design, implement, and maintain end-to-end ML pipelines using Databricks notebooks, Delta Lake, and MLflow for experiment tracking, model versioning, and lifecycle management.

• Leverage Databricks AutoML for rapid prototyping and efficient model selection in early-stage experimentation.

• Implement ML model deployment workflows using Databricks Jobs and manage serving endpoints with low-latency requirements.

• Design, develop, and deploy ML and GenAI solutions using Python and LLM frameworks.

• Build and deploy ML production systems, contributing to their design and ongoing maintenance

• Develop and maintain ML pipelines, manage the data lifecycle, and ensure data quality and consistency throughout

• Assure robust implementation of ML guardrails and manage all aspects of service monitoring

• Develop and deploy accessible endpoints, including web applications and REST APIs, while maintaining steadfast data privacy and adherence to security best practices and regulations

• Embrace agile development practices, valuing constant iteration, improvement, and effective problem-solving in complex and ambiguous scenarios

• Collaborate with cross-functional teams including architects, data engineers, analysts, and business leaders to deliver robust data solutions.

• Write and maintain infrastructure as code using YAML, Implement and manage CI/CD pipelines for ML workflows.

• Ensure model governance and compliance using protocols like Model Context Protocol and A2A Protocol.

• Produce comprehensive documentation including architectural diagrams, data flow maps, runbooks, and lineage tracking artifacts.

• Continuously improve ml pipeline efficiency by identifying performance bottlenecks and reducing compute/storage costs.

• Containerize applications using Docker and manage deployments on Azure

• Implement DevOps best practices in the data lifecycle, including CI/CD for pipelines, automated testing, and version control.

• Facilitate internal knowledge sharing via technical workshops, peer reviews, and training sessions for continuous team development.

About You:

The ideal candidate for this position will have the following experience and qualifications:

• A bachelor's degree in computer science, information technology, or a related field is required; a master's degree is preferred but not mandatory.

• A minimum of 3-5 years of hands-on experience in Python software development with a focus on modular, scalable, and efficient coding for AI/LLM-based applications.

• Proven track record of building, scaling, and leading complex ML engineering platforms in enterprise environments.

• Strong experience designing and deploying cloud-native ML solutions on Azure Databricks, with an emphasis on scalable model training, model management using MLflow, and real-time inference.

• Demonstrated success in implementing AI agents or autonomous workflows using tools such as LangGraph, CrewAI, or similar frameworks.

• Experience in real-time or near-real-time inference systems and low-latency model serving.

• Hands-on experience with Databricks Machine Learning environment, including MLflow tracking, model registry, and production deployment workflows.

• Proficient in using Databricks Feature Store, AutoML, and real-time model inference using Databricks Serving or external endpoints.

• Familiarity with Databricks Unity Catalog and access control for secure ML asset management.

• Advanced proficiency in Python and LLM, with strong skills in performance tuning, modular coding, and automation scripting

• Experience deploying GenAI & related frameworks (e.g., LangChain, LLMOps, PaLM) use cases in Snowflake ecosystem

• Develop, optimize, and maintain scalable machine learning workflows and models using Databricks notebooks and MLflow.

• Understanding of how MCPs can complement structured Snowflake data to deliver rich narrative insights, automated clinical summaries, and patient engagement tools.

• Build AI-driven applications using Snowflake Cortex, Document AI, and Snowpark ML.

• Integrate GenAI tools like OpenAI GPT, Claude (Anthropic), and xAI s Grok to enhance unstructured data processing and generate intelligent summaries or decision recommendations.

• Experience in experimentation, feature engineering, Model registration, deployment, and monitoring, using AutoML cost and quota management

• Strong written and verbal communication skills in English, with the ability to influence, mentor, and align technical teams and stakeholders.

• Candidates with coursework or academic research in deep learning, reinforcement learning, or natural language processing are highly encouraged.

• Databricks Certified Machine Learning Professional

• Snowflake SnowPro Core Certification

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