Machine Learning Eng. (GenAI & Enterprise Systems)
Tasks
- Build and optimize data and model pipelines
- Collaborate to transition prototypes into production solutions
- Design and implement end to end ML and GenAI systems
- Design model serving solutions and API integration patterns
- Develop scalable RAG architectures and LLM integrations
- Implement automated testing and evaluation frameworks for ML and LLM
- Optimize model performance for latency, throughput, and cost
- Productionize ML and LLM models with reliability and observability
Perks/Benefits
Skills/Tech-stack
AWS | Automated testing | Azure | CI/CD | Cost Optimization | Distributed Systems | Evaluation Frameworks | GCP | Language Models | Large Language Models | Latency optimization | Machine Learning | Model Deployment | Model Monitoring | Observability | PyTorch | Python | REST APIs | Reliability | Retrieval-Augmented Generation | Scalable architectures | Scikit-learn | TensorFlow | Throughput Optimization
Education
N/A
Regions
Countries
States
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