Machine Learning Engineer
Tasks
- Automate issue detection and resolution
- Build AI evaluation frameworks
- Build AI-powered systems
- Cluster patterns to identify recurring failures
- Collaborate with SREs and product teams
- Contribute to code reviews testing and documentation
- Create agentic workflows for safe production execution
- Deploy ML models to backend services
- Design and implement LLM-based workflows
- Develop knowledge systems using vector embeddings
- Forecast time series demand and capacity
- Integrate AI with production infrastructure
- Maintain CI CD pipelines for ML systems
- Monitor model performance and safety guardrails
- Perform anomaly detection on operational data
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Anomaly Detection | Atlas Vector Search | B testing | ChromaDB | Classification | Clustering | Evaluation metrics | F1-score | Faiss | FastAPI | Flask | GitHub Actions | Huggingface | Kubernetes | LLM Agents | Langchain | Model Deployment | MongoDB Atlas | MongoDB Atlas Vector Search | OpenAI API | Pinecone | Precisión | Prometheus | Prompt engineering | PyTorch | Python | Recall | Scikit-learn | Series forecasting | Similarity Search | Splunk | TensorFlow | Time Series | Time Series Forecasting | Vector Search | Vector embeddings
Education
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