Senior AI Engineer
Tasks
- Architect and lead backend APIs and microservices for AI workloads
- Collaborate with data scientists to implement AI requirements
- Define and enforce API and security design standards
- Drive end to end AI pipeline engineering for model training and inference
- Implement MLOps and DevSecOps best practices
- Improve platform capabilities with monitoring and emerging technologies
- Integrate AI/ML solutions with enterprise infrastructure
- Lead architectural discussions and conduct code reviews
Perks/Benefits
- Career development and training
- Confidential counseling support
- Employee wellness centers
- Financial coaching
- Health insurance
- Hybrid work
- Paid parental leave
- Retirement plan match
Skills/Tech-stack
API Design | API Versioning | AWS | Argo Workflows | Authentication & Authorization | Autogen | Azure | Distributed Systems | Django | Docker | Elasticsearch | FastAPI | Flask | GCP | GRPC | GitHub Actions | GitLab CI | GraphQL | Hugging Face | Inference Server | JWT | Jenkins | Kafka | Kibana | Kubeflow | Kubernetes | Langchain | MLflow | Microservices | Nifi | NoSQL | OAuth2 | OpenAPI Swagger | PostgreSQL | Prometheus | PyTorch | Python | REST | SQL | Scikit-learn | Service orchestration | Spark | TensorFlow | Triton Inference | Triton Inference Server | Vault
Education
Roles
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