Machine Learning Engineer 727
Tasks
- Build production inference pipelines
- Build scalable APIs for AI capabilities
- Deploy AI workloads to AWS cloud environments
- Design train validate deploy machine learning models
- Develop feature engineering workflows
- Document processes and integration patterns
- Gather document and refine customer requirements
- Implement MLOps pipelines
- Implement integration solutions
- Monitor model drift and operational performance
- Optimize model performance and resource utilization
- Support computer vision NLP and geospatial AI initiatives
Perks/Benefits
- 401k match
- Annual logo wear allowance
- Company-sponsored events
- Flexible work environment
- Fully paid medical
- Paid life and disability
- Paid site closure days
- Paid time off
- Paid training
- Referral bonuses
- Tuition reimbursement
- Work-life balance
Skills/Tech-stack
AWS EKS | AWS Lambda | Agile | Amazon Aurora | Amazon ElastiCache | Amazon SageMaker | CI/CD | Computer Vision | Continuous Deployment | Continuous integration | Docker | ECS | Feature Engineering | GDAL | Geospatial AI | GitLab CI | GitLab CI/CD | Hugging Face | Kubernetes | Language Processing | Linux | MLOps | MLflow | Natural Language | Natural Language Processing | OGR | Oracle | Podman | PostGIS | PostgreSQL | PyTorch | Python | REST API | Rasterio | Redis | Satellite imagery | Scikit-learn | TensorFlow
Education
N/A
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