Senior Software Engineer, Data Systems
Tasks
- Build LLM powered enrichment classification pipelines
- Build data pipelines and infrastructure
- Build data products with production APIs
- Build observability for model degradation
- Create feature stores and training pipelines
- Define data SLAs and monitor data health
- Deploy and monitor ML systems for drift and data quality
- Design ML platform from experiment to production
- Design cloud data platform
- Develop low latency feature access
- Ensure scalable distributed systems performance
- Implement data validation transformation denormalization
- Implement model serving and monitoring
- Own change data capture pipelines
- Troubleshoot distributed data and ML systems
Perks/Benefits
- Dental coverage
- Flexible work hours
- Fully remote
- Health insurance
- Parental leave top-ups
- Unlimited PTO
- Work-life balance
Skills/Tech-stack
Airflow | Amazon Redshift | Apache Kafka | Backpressure | Capacity Planning | Change Data Capture | ClickHouse | Clustering | Consistency models | Cross-validation | Dagster | Data Capture | Data Pipelines | Data Quality | Distributed Systems | Django | Drift monitoring | Elasticsearch | Experiment tracking | Fault Tolerance | Feature Engineering | Feature Store | LLMs | Low Latency | Low-Latency Systems | MLOps | Machine Learning | Model Drift | Model Monitoring | Model Registry | Model Serving | Model drift monitoring | MongoDB | MySQL | Observability | Pandas | Prompt engineering | PyTorch | Python | Regression | Regularization | Scikit-learn | Supervised Learning | TensorFlow | Tree ensembles | Unsupervised Learning
Education
N/A
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