AI/ML & Forward Deployed Engineer
Tasks
- Apply data quality governance security RBAC encryption and auditability controls
- Build and optimize deep learning NLP and forecasting models
- Build scalable AI services using REST and gRPC and event driven architectures
- Collaborate with stakeholders to translate business requirements into AI solutions
- Containerize and orchestrate AI applications with Docker and Kubernetes and CI CD pipelines
- Design machine learning AI and GenAI solutions from proof of concept to production
- Develop GenAI applications using LLMs and RAG pipelines
- Establish MLOps and LLMOps practices for deployment automation versioning and monitoring
- Implement AI evaluation frameworks for model quality reliability and performance
- Implement model monitoring drift detection and continuous improvement
- Support production operations troubleshooting optimization and continuous enhancements
Perks/Benefits
Skills/Tech-stack
Access Control | Anomaly Detection | CI/CD | Classification | Data Governance | Deep learning | Docker | Drift Detection | Embeddings | Encryption | Event Driven | Event-driven architecture | Forecasting | GRPC | Kubernetes | LLMOps | Language Models | Language Processing | Large Language Models | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Evaluation | Model Monitoring | Model versioning | Natural Language | Natural Language Processing | Observability | Prompt engineering | Python | REST APIs | Regression | Reranking | Retrieval-Augmented Generation | Role-Based Access | Role-Based Access Control
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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