Engineering-Applied Science/Machine Learning/Data Science
Tasks
- Build ML pipelines and microservices
- Collaborate with cross-functional teams
- Deploy and monitor machine learning models
- Design and implement scalable ML systems
- Develop and optimize LLM applications
- Establish best practices for AI safety and reliability
- Lead AI strategy and research innovation
- Mentor applied scientists and engineers
- Translate prototypes into production-ready services
Perks/Benefits
Skills/Tech-stack
API Design | Airflow | CI/CD | Data Pipelines | Deep learning | Distributed Computing | Docker | Flink | Git | Grafana | Kafka | Keras | Kubernetes | Langchain | Language Models | Language Processing | Large Language Models | Llamaindex | MLflow | Machine Learning | Model Deployment | Natural Language | Natural Language Processing | Observability | OpenAI API | Prometheus | PyTorch | Python | SQL | Spark | TensorFlow | Version control
Education
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