Senior Machine Learning Engineer
Tasks
- Build genai agents for log trace and metric analysis
- Deploy and monitor models in production on Kubernetes
- Design multi agent systems using reinforcement learning loops
- Develop deep learning models for forecasting and anomaly detection
- Engineer model feature pipelines for large scale training and monitoring
- Optimize inference pipelines for low latency streaming telemetry
- Translate research into production hardened AIOps tools
Perks/Benefits
- Compassionate care leave
- Health benefits
- Learning and development
- Paid parental leave
- Paid time off
- Retirement plans
Skills/Tech-stack
AWS | Agent systems | Apache Spark | Azure | CI/CD | Causal Inference | Control Theory | FastAPI | Feature Engineering | Flink | GCP | Grafana | Inference Optimization | Inference Server | Jaeger | Kafka | Kubernetes | Langchain | Language Models | Language Processing | Large Language Models | Long Short | Long Short-Term Memory | Machine Learning | Multi-Agent | Multi-Agent Systems | Natural Language | Natural Language Processing | OpenTelemetry | Prometheus | PyTorch | Python | Ray RLlib | Reinforcement Learning | Retrieval-Augmented Generation | Series analysis | Short Term Memory | TensorFlow | Time Series | Time Series Analysis | Transformers | Triton Inference | Triton Inference Server | Vector Databases
Education
N/A
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