Senior AI Engineer
Tasks
- Apply reinforcement learning techniques for continuous learning and online optimization
- Collaborate with product teams and engineering teams to deliver customer experiences
- Deploy ML inference services for real time or high throughput applications
- Design scalable low latency ML systems
- Implement model training inference and deployment infrastructure
- Integrate and operationalize machine learning models into production
- Optimize ML pipeline performance and real time responsiveness
- Support machine learning project lifecycle from experimentation to deployment
Perks/Benefits
- 401k match
- Adoption reimbursement
- Comprehensive onboarding
- FSA and HSA
- Fertility services support
- Financial planning tools
- Flexible time off
- Flextime
- Leadership training
- Learning and development opportunities
- Legal advisory services
- Medical, dental & vision coverage
- Parental leave
- Pet insurance
- Telehealth Memberships
- Telehealth options
Skills/Tech-stack
AIOps | AWS | AWS Lambda | Amazon Redshift | Asynchronous Messaging | Azure Cloud | Azure Cognitive | Azure Cognitive Services | Azure Functions | Azure Service | Azure Service Bus | Cognitive Services | Debugging | Deep learning | Forecasting | Git | Jira | Kafka | Language Processing | Low Latency | Low-Latency Systems | MLOps | Machine Learning | Microservices | Model Deployment | Natural Language | Natural Language Processing | PostgreSQL | Profiling | Python | Recommender Systems | Reinforcement Learning | SQL Server | Serverless architecture | Service Bus | Snowflake | Speech Processing | Unit Testing
Education
N/A
Roles
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