Senior AI/ML Engineer
Tasks
- Build and operate LLM pipelines
- Create tooling for experimentation deployment and monitoring
- Define success metrics and deliver high impact solutions
- Deploy and monitor ML models in production
- Design model evaluation frameworks
- Design scalable machine learning systems
- Develop RAG systems
- Ensure reliable and scalable ML systems with platform teams
- Establish reproducibility observability CI CD and model versioning
- Lead cross-functional ML initiatives
- Own end-to-end ML lifecycle
- Promote responsible AI governance fairness transparency
- Provide technical mentorship and drive team upskilling
- Scope and lead AI ML initiatives
- Translate ML concepts for technical and non technical audiences
- Translate prototypes into production systems
Perks/Benefits
Skills/Tech-stack
AWS | Azure | AzureML | Bedrock | CI/CD | Code review | Data Pipelines | Databricks | Deployment | Embeddings | Experiment tracking | Fine Tuning | Huggingface | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Fine-tuning | Model versioning | Modularity | Monitoring | Observability | Prompt engineering | PyTorch | Python | Reproducibility | Responsible AI | Retrieval-Augmented Generation | SQL | SageMaker | Snowflake | Testing | Training | Vector Search
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer | Senior AI/ML Engineer
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