AI/ML & Forward Deployed Engineer
Tasks
- Build optimize deep learning and machine learning models
- Build scalable AI services using REST and gRPC
- Collaborate with stakeholders to translate requirements into technical solutions
- Containerize and orchestrate AI applications using Docker and Kubernetes
- Design deploy AI and GenAI solutions from proof of concept through production
- Develop GenAI applications using LLMs and RAG pipelines
- Ensure data quality governance security RBAC encryption and auditability
- Establish MLOps and LLMOps practices for deployment automation and versioning
- Implement AI evaluation frameworks for model quality and reliability
- Implement model monitoring drift detection and performance tracking
- Support production operations troubleshooting and continuous improvements
Perks/Benefits
Skills/Tech-stack
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 | Natural Language | Natural Language Processing | Prompt engineering | Python | RBAC | REST | Regression | Retrieval-Augmented Generation
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | MLOps Engineer | Machine Learning Engineer
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