AI/ML & Forward Deployed Engineer
Tasks
- Automate deployment and monitoring
- Build AI evaluation frameworks
- Build REST and gRPC APIs
- Build and optimize NLP models
- Build and optimize anomaly detection models
- Build and optimize classification models
- Build and optimize forecasting models
- Build and optimize regression models
- Build event-driven architectures
- Containerize applications
- Create embeddings and retrieval optimization
- Deploy machine learning and AI systems
- Design and develop machine learning solutions
- Develop AI services and integrations
- Develop generative AI applications
- Ensure data quality and governance
- Implement MLOps and LLMOps practices
- Implement model monitoring and drift detection
- Implement reranking and prompt engineering
- Implement retrieval-augmented generation pipelines
- Implement security controls RBAC and encryption
- Orchestrate services with Kubernetes
- Set up CI/CD pipelines
- Support production operations and troubleshooting
- Track model performance and reliability
Perks/Benefits
Skills/Tech-stack
Anomaly Detection | Artificial Intelligence | Audit Logging | CI/CD | Classification | Deep learning | Docker | Drift Detection | Embeddings | Encryption | Event Driven | Event-driven architecture | Forecasting | GRPC | Generative AI | Kubernetes | LLM | LLMOps | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model versioning | NLP | Natural Language | Natural Language Processing | Prompt engineering | Python | RAG | RBAC | REST APIs | Regression | Reranking | Retrieval tuning | Retrieval-Augmented Generation
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | MLOps Engineer | Machine Learning Engineer
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