**Salary for this position is between 150-165K depending on years of experience
**Candidates are expected to be fluent in GCP and have used GCP AI tools
Develop and maintain a data exploration and feature engineering pipeline to enable data readiness for modeling within a secure and compliant infrastructure.
Implement and manage Databricks, JupyterHub, and other modern tools for exploratory data analysis, AI design, model development, and training.
Integrate tools with Bitbucket for version control and collaboration.
Establish and maintain a model development pipeline utilizing MLflow for experiment tracking and model registry.
Experience with AI tools for GCP; Vertex AI, Document AI, NotebookLM, BigQuery ML, Gemini
Create GCP functions and implement GCP for efficient model artifact storage and metadata management.
Integrate with GCP for robust data management and retrieval.
Configure SNS notifications for model promotion workflows.
Support data science teams in adhering to Responsible AI Principles via the implementation of the Responsible AI Toolbox.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal. com.
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Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field and 7 years experience.
Proven experience with cloud services, particularly GCP
Expertise in setting up and managing data science environments with tools such as Databricks, JupyterHub, MLflow, and Bitbucket.
Strong proficiency in programming languages and tools such as SQL, Python, R, and Spark.
Familiarity with machine learning frameworks and libraries.
Deep understanding of data security and privacy
Experience with CI/CD pipelines and infrastructure as code.