Sr. Machine Learning/AI Engineer
Tasks
- Build and deploy machine learning models
- Create Agent workflows
- Deploy APIs and microservices
- Develop LLM-powered applications
- Develop automated decision support tools
- Ensure data availability and ML readiness
- Evaluate new AI tools and frameworks
- Implement MLOps workflows
- Implement rag pipelines
- Maintain security safety and compliance
- Mentor engineers and analysts
- Monitor model performance and governance
- Present solution designs to stakeholders
- Translate business needs into AI solutions
Perks/Benefits
Skills/Tech-stack
A/B | A/B Testing | API Development | AWS | Amazon Redshift | Amazon SageMaker | Azure Synapse | Azure Synapse Analytics | B testing | Containerization | Databricks | Distributed Systems | Embeddings | Fine Tuning | Google BigQuery | Kubernetes | Langchain | Language Models | Large Language Models | MLOps | MLflow | Microservices | Model Governance | Model Monitoring | Model Optimization | Observability | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | Scikit-learn | Snowflake | Statistical modeling | Synapse Analytics | TensorFlow | Transformers | Vector Databases | Weights and Biases
Education
N/A
Regions
Countries
States
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