Senior ML Engineer (GenAI, AWS)
Tasks
- Build reusable machine learning accelerators
- Build scalable machine learning pipelines and infrastructure
- Collaborate with cross-functional teams
- Conduct experimentation and model evaluation
- Deploy machine learning models to production environments
- Design and implement end-to-end machine learning solutions
- Document and present machine learning knowledge
- Mentor junior and mid level machine learning engineers
- Optimize model performance efficiency and reliability
- Participate in technical discussions and architecture decisions
- Perform code reviews and provide feedback
- Propose improvements to existing solutions and processes
- Set up model monitoring and observability
- Stay current with machine learning research and technologies
- Track experiments with MLflow or Weights and Biases
- Troubleshoot and resolve technical challenges
- Write production quality code for machine learning
Perks/Benefits
- AWS certification sponsorship
- Continuous learning support
- Medical insurance
- Paid public holidays
- Paid sick leave
- Paid vacation
- Remote work
Skills/Tech-stack
AWS | AWS Lambda | Amazon SageMaker | CI/CD | CloudFormation | Deep learning | Docker | ELT | ETL | MLflow | Machine Learning | Model Monitoring | NumPy | Observability | Pandas | Prompt engineering | PySpark | PyTorch | Python | RAG | Reinforcement Learning | Retrieval-Augmented Generation | SQL | Spark | TensorFlow | Terraform | Transformers | Vector Databases | Vector Search | Weights and Biases
Education
N/A
Roles
DevOps | DevOps Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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