Note: The job is a remote job and is open to candidates in USA. ShiftCode Analytics, Inc. is seeking a highly skilled Senior Machine Learning Engineer to join its Data Science & Analytics organization. This backend-focused role involves building and operationalizing scalable AI/ML systems in production environments, collaborating closely with Data Scientists and Engineers to enhance Hyatt's digital ecosystem.
Responsibilities
- Design and implement scalable backend architectures supporting machine learning products
- Build and operationalize AI/ML services across the full product lifecycle: Data ingestion, Feature engineering, Model integration, Real-time inference, Batch processing, Deployment and monitoring
- Partner closely with Data Scientists to productionize machine learning models
- Develop streaming and batch data processing workflows at scale
- Implement infrastructure-as-code and CI/CD deployment pipelines
- Enhance and maintain feature store workflows and ML data pipelines
- Optimize latency, scalability, and reliability of ML systems
- Build services supporting personalization, recommendation engines, search, analytics, and conversational AI experiences
- Collaborate with Data Engineering, Architecture, Governance, and Security teams
- Support cloud-native ML infrastructure within AWS and Google Cloud environments
- Contribute to system design discussions and technical architecture decisions
Skills
- 5+ years of software engineering experience implementing cloud-native product solutions
- Strong experience building backend systems supporting ML/algorithmic products
- Expertise with: Python
- Expertise with: SQL
- Expertise with: PySpark
- Expertise with: Docker
- Strong AWS cloud experience
- Experience with Google Cloud Platform (GCP)
- Experience building streaming and batch data architectures at scale
- Strong system design and backend architecture experience
- Experience operating in Agile environments
- Experience with DevOps and CI/CD practices
- Ability to handle ambiguity and rapidly changing requirements
- Strong communication and collaboration skills
- Experience with SageMaker
- Understanding of feature stores
- Hospitality or personalization/recommendation system experience
- Real-time ML inference and personalization systems
- Infrastructure-as-code implementation experience
- Experience supporting AI/LLM-enabled applications
- Master's degree in Computer Science, Software Engineering, or related field
- Bachelor's degree + strong equivalent experience acceptable
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