Senior Machine Learning/MLOps Engineer (Remote Opportunity)

About the position Responsibilities • Partner with data scientists to design AI-services and architectures that activate ML models and maximize their impact, such as real-time streaming use-cases and offline batch optimizations • Lead the design and implementation of ML infrastructure solutions, including data ingestion pipelines, feature processing, model training, and serving environments • Build and maintain scalable inference systems for real-time and batch predictions • Deploy models across various compute environments (EC2, EKS, SageMaker, specialized inference chips) • Implement, evolve, and maintain our MLOps platform, technology, and processes; including Feature Store, ML Observability, ML Governance, Training and Deployment pipelines • Create and maintain automated workflows for model training, evaluation, and deployment using infrastructure-as-code patterns • Build MLOps platforms and tooling that abstract complex engineering tasks for data science teams • Implement CI/CD pipelines for both model artifacts and infrastructure components • Design, implement, and optimize machine learning models including deep learning architectures, LLMs, and specialized models (e.g., BERT-based classifiers) across Personalization, Generative AI, Forecasting, and Decision Science domains • Implement distributed training workflows using PyTorch and other frameworks • Fine-tune large language models and optimize inference performance using model compilation and optimization tools (Neuron compiler for AWS Inferentia, ONNX, vLLM) • Optimize models for specific hardware targets (GPU, TPU, AWS Inferentia/Trainium) • Enhance and maintain existing AI-services as needed to maximize impact of the algorithmic product • Monitor ML systems for performance, accuracy, latency, and cost optimization • Conduct performance profiling and optimization of training and inference workloads • Implement observability and monitoring solutions across the ML stack • Partner with data engineering team to ensure data science data needs are being delivered in the appropriate format/cadence required for maximum impact • Partner with data architecture, data governance, and security team to ensure solutions meet required standards • Mentor team members on both modeling techniques and infrastructure best practices • Stay up to date with latest AI and MLOps design patterns as well as AWS services with respect to Machine Requirements • Master's degree in Computer Science, Software Engineering, Machine Learning, or related fields required • 5 years of implementing AI solutions in a cloud environment with a focus on AI-services and MLOps foundations. Hospitality experience not required • 3 years of hands-on experience with both ML model development and production infrastructure • Cloud & Infrastructure: Expertise in AWS cloud services (EC2, EKS, S3, SageMaker, Inferentia/Trainium), Terraform/CloudFormation, Docker, Kubernetes • Data & Processing: Expertise in Python, SQL, PySpark, Apache Spark, Airflow, Kinesis, feature stores, model serving frameworks • Development & Operations: Experience with streaming and batch data architectures at scale, DevOps and CI/CD concepts (GitHub Actions, CodePipeline), monitoring (CloudWatch, Prometheus, MLflow) • Machine Learning & Deep Learning: PyTorch, TensorFlow, distributed training, LLM fine-tuning, transformer architectures, model optimization, ONNX, vLLM, hardware-specific optimizations • Experience operating in an Agile Methodology environment • Experience building end-to-end ML systems from research to production • Excellent communication and teamwork skills • Position will not require customer-facing interactions Nice-to-haves • Previous work on recommendation systems, NLP applications, or real-time inference systems • Experience with MLOps platform development and feature store implementations • Familiarity with security and compliance standards in cloud environments Benefits • Annual allotment of free hotel stays at Hyatt hotels globally • Flexible work schedule and location • Work-life benefits including wellbeing initiatives such as a complimentary Headspace subscription, and a discount at the on-site fitness center • A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption • Paid Time Off, Medical, Dental, Vision, 401K with company match Apply tot his job