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Senior Machine Learning Engineer – Data Science & Analytics
Strong candidates will demonstrate:
- Exceptional software engineering and computer science fundamentals
- Experience building scalable backend systems supporting ML workloads
- Ability to architect, deploy, and maintain production-grade AI/ML services
- Comfort working in ambiguous and evolving environments
- Strong analytical and systematic problem-solving skills
- Fast learning ability and intellectual curiosity
- Experience collaborating cross-functionally with Data Scientists and Engineering teams
- Proven delivery experience in enterprise or high-scale technology environments
Candidates with pure data science or research-heavy backgrounds are less aligned unless they possess strong production engineering experience.
- 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
- 5+ years of software engineering experience implementing cloud-native product solutions
- Strong experience building backend systems supporting ML/algorithmic products
- Expertise with:
- Python
- SQL
- PySpark
- 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
- Team uses existing LLMs rather than building foundational models
- Master's degree in Computer Science, Software Engineering, or related field
- Bachelor's degree + strong equivalent experience acceptable
- Python
- SQL
- PySpark
- Docker
- AWS
- GCP
- Real-time personalization
- Recommendation systems
- Search platforms
- Internal analytics tooling
- Chat interfaces and AI-assisted workflows
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