
Data Scientist Role
1 week ago
We are seeking an experienced Machine Learning Engineer to design, develop, and deploy machine learning models and pipelines that drive business growth and improvement.
The successful candidate will be responsible for designing, developing, and deploying machine learning models and pipelines that drive business growth and improvement.
This is a key role in our technology team, requiring a strong foundation in machine learning concepts and techniques, proficiency in Python programming language, experience with cloud-based platforms like AWS, knowledge of DevOps practices and CI/CD pipelines, and the ability to work collaboratively as part of a cross-functional team.
Required Skills and Qualifications- 5+ years of Python experience in scripting ML workflows for real-time, batch, event-triggered, and edge deployments
- 4+ years of experience using AWS SageMaker for deployment of ML pipelines and ML models using SageMaker Pipelines, SageMaker MLflow, and SageMaker Feature Store
- 3+ years of development experience with APIs using FastAPI, Flask, and Django
- 3+ years of experience with ML frameworks and tools like scikit-learn, PyTorch, xgboost, lightgbm, and mlflow
- Solid understanding of the ML lifecycle, including model development, training, validation, deployment, and monitoring
- Experience with CI/CD pipelines specifically for ML workflows using Bitbucket, Jenkins, Nexus, and Autosys for scheduling
- Experience with ETL processes for ML pipelines using PySpark, Kafka, and AWS EMR Serverless
- Good-to-have experience with H2O.ai and containerization using Docker and orchestration using Kubernetes
- A dynamic and collaborative work environment
- Ongoing opportunities for professional growth and development
- A competitive salary and benefits package
- The chance to work on exciting projects that drive business impact
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