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