Senior AI/ML Engineer
Tasks
- Build and operate LLM pipelines
- Create evaluation frameworks and feedback loops
- Deploy and monitor ML models
- Design prompt tuning and model fine tuning
- Design scalable machine learning systems
- Develop RAG systems with embeddings and vector search
- Establish reproducibility and observability best practices
- Implement CI/CD and model versioning
- Lead cross-functional AI/ML initiatives
- Lead technical mentorship and team upskilling
- Own end-to-end machine learning lifecycle
- Promote responsible AI governance fairness and transparency
- Scope and execute complex AI ML projects with success metrics
- Translate ML concepts for technical and non technical audiences
- Translate research prototypes to production systems
Perks/Benefits
Skills/Tech-stack
AWS | Azure | Azure Machine Learning | Bedrock | CI/CD | Code review | DPO | Data Pipelines | Databricks | Deep learning | Embeddings | Evaluation | Experiment tracking | Experimentation | Fine Tuning | Huggingface | Language Models | Large Language Models | MLOps | Machine Learning | Model Monitoring | Model versioning | Modularity | Observability | Prompt design | Prompt engineering | PyTorch | Python | RAG | RLHF | Reproducibility | Retrieval strategies | Retrieval-Augmented Generation | SFT | SQL | SageMaker | Snowflake | Testing | Training | Vector Databases | Vector Search
Education
N/A
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