Machine Learning Engineer
Tasks
- Build Agentic AI workflows
- Build Retrieval Augmented Generation systems
- Build regression suites
- Collaborate with data and platform engineers
- Communicate model tradeoffs to stakeholders
- Create feature stores and serving infrastructure
- Create tool using agents
- Deploy machine learning systems
- Design human in the loop pipelines
- Design offline and online evaluations
- Develop foundation model applications
- Explore data and build features
- Frame business problems for ML
- Implement multi-agent systems
- Iterate models using real world signals
- Maintain CI CD for ML
- Mentor engineers and lead design reviews
- Monitor model performance
- Own ML projects end-to-end
- Partner on MLOps pipelines
- Run A/B tests
- Set technical direction for ML stack
- Train and evaluate predictive models
- Use LLM as judge
Perks/Benefits
- N/A
Skills/Tech-stack
A/B | A/B Testing | Anomaly Detection | B testing | CI/CD | Computer Vision | Databricks | Experiment tracking | Fine Tuning | Function Calling | Hugging Face | JAX | LLMOps | Language Models | Language Processing | Large Language Models | LightGBM | MLOps | Model Monitoring | Multimodal | Natural Language | Natural Language Processing | NumPy | Pandas | Prompt engineering | PySpark | PyTorch | Python | Random Forest | Regression | Retrieval-Augmented Generation | Scikit-learn | Series forecasting | Structured outputs | Time Series | Time Series Forecasting | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Regions
Countries
States
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