Python, Data Science, Data Engineering, MLOPS, FastAPI, Pandas, TensorFlow, xgBoost, PySpark, Big Query, CI/CD, ML Frameworks, Google Cloud Eco System
Design, develop, and implement generative AI architectures, models, and solutions that meet customer needs and align with industry best practices.
10+ years
Job Description:
- Experience as a ML Engineer, with fluency and experience in Python, Data Science, Data Engineering & MLOPS
- Knowledge in RESTful API design and implementation
- Experience of Web framework like FastAPI/Tornado/Flask etc.
- Data Science knowledge and familiarity with ML libraries such as Pandas, Scikit, TensorFlow, xgboost, time series frameworks like prophet/or equivalent frameworks
- In-depth of big data frameworks like Pyspark & Google Cloud Platform tools like data proc, data proc serverless
- Experience designing, building and operating productions grade ML applications
- Knowledge of design patterns and architecture, data science, and machine learning best practices
- Experience with relational databases like Big Query, cloud environments, and a good understanding of optimizing storage cost/query cost while designing data engineering workflows
- Good knowledge of Kubernetes, container technologies, docker registries, and applying them in the context of machine learning systems
- Working knowledge of ML frameworks, such as Vertex, Kubeflow, MLflow, CloudRun etc.
- Experience in designing post-deployment model management framework e.g. model monitoring tools, workflows for feature drift, error analysis of models
- Proficiency with CI/CD tools, especially Jenkins
- Experience in designing CI/CD pipelines (Jenkins) for deployment of Data Engineering and ML jobs workflow
- Hands-on experience in orchestration frameworks like Airflow, Cloud Composer, DataProc Serverless for Pyspark jobs etc.
- In-depth understanding of Google Cloud ecosystem for Data Engineering & MLOps - cloud composer, dataproc, dataproc serverless, big query, cloudrun, vertex, vertex pipelines, GKE
- Experience in designing MLOps platforms and architect big data systems on Google Cloud Platform cloud