What You’ll Do
- This role is critical in making ML and AI services to power engaging user experiences
- Working from end-to-end on live production services. Not just modeling, not theoretical
- The work you do will directly impact our customers' day-to-day experiences
- Define the best approach to solve problems with ML. Build data and model pipelines
- Test and Validate services. Deploy and monitor solutions for impact
- Work within a cross-functional application team to build scalable language services in the range of NLP, NLU, and NLG for live SaaS products
- Help develop and groom an experiment backlog
- Build models that solve real-world problems
- Optimize models for production throughput and uptime requirements
- Automate deployments, testing, and monitoring (MLOps)
Requirements
- 5+ years of developing data & analytics products like sentiment analyzers, translation engines, summarizers, or other language services
- Expert in Machine Learning, Modeling, and development with Python
- Expert in MLOps with at least one platform, e.g.: MLflow, Kubeflow, or end-to-end automation with SageMaker services
- Ability to mentor others and work independently
- Strong communication skills
Nice to Have
- Production experience with any of the following is a plus: GenAI, LLMs, Recommendation Engines, AWS offerings for AI and ML including SageMaker, Bedrock, Lex
- Knowledge of relevant regulations in AI/ML and incorporating compliance into MLOps processes
- Bachelor’s degree or higher in computer science, engineering, or information systems
