MLOps Engineer
3 weeks ago
Tiger Analytics is a leading advanced analytics consulting firm that is looking for experienced Machine Learning Engineers to join our team. Our employees bring deep expertise in Machine Learning, Data Science, and AI, and we are the trusted analytics partner for multiple Fortune 500 companies. We enable our clients to generate business value from data, and our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
We are looking for top-notch talent to continue building the best global analytics consulting team in the world. As a Machine Learning Engineer, you will be responsible for:
- Developing and deploying machine learning models using AWS SageMaker, AWS CFT, and AWS CodePipeline.
- Building and testing data pipelines using Apache Airflow and Docker.
- Implementing monitoring solutions using Lambda and Dash.
- Developing data quality solutions using Great Expectations.
Requirements:
- Bachelor's degree or higher in computer science or a related field, with 5+ years of work experience.
- Ability to collaborate with Data Engineers and Data Scientists to build data and model pipelines.
- Experience in AWS, including SageMaker, Lambda, and CloudFormation.
- Knowledge of traditional ML models, Python, Spark, Hadoop, and Docker.
- Experience with ML frameworks like Scikit-learn, TensorFlow, and Keras.
Additional Skills:
- Knowledge of database and data engineering concepts.
- Experience with Oracle, Spark, Hadoop, Athena, API, FastAPI, Flask, and ReST.
- Knowledge of MLflow, Airflow, and Kubernetes.
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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