Machine Learning Engineer (All Levels)
Tasks
- Build batch and stream data pipelines
- Collaborate across software systems and product teams
- Design evaluation pipelines
- Implement MLOps and LLMOps workflows
- Mentor and guide technical decisions
- Own and ship ML in production
- Own end to end data curation feature engineering training evaluation deployment monitoring
- Profile optimize and debug ML systems
- Run and improve training and inference at scale
- Train and adapt models
Perks/Benefits
Skills/Tech-stack
AWS | Apache Spark | CI/CD | Code review | Computer Vision | DDP | Databricks | Debugging | Deep learning | DeepSpeed | Delta Lake | Distributed Training | Docker | Experiment tracking | Fine Tuning | GCP | GitHub | Inference Optimization | Kubernetes | LLMOps | Language Models | Language Processing | Large Language Models | MLOps | MLflow | Machine Learning | Megatron | Model Evaluation | Model Registry | Model Training | NVIDIA Jetson | Natural Language | Natural Language Processing | Observability | Optimization | Probability | PyTorch | Python | Raspberry Pi | RunAI | SQL | Slurm | Testing | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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