cloudrann
Data Scientist
Remote
Indent: PSL304601-16-1
Only GC AND GCEAD,H4EAD,USC,TN – VISAS
Please check below questions before submitting
Data Science on GCP
Very well hands-on on any Tensorflow / Pytorch
Kubeflow / tensorflow Pipeline
Vertex AI; Feature Engineering, MLOps, Model Versioning and Endpoint Deployment
Very well hands-on on Neural Networks
Note to tell – LLM or GenAI based solution is not approved by customer so we will have to build using traditional Machine learning techniques.
Detailed JD:
Designs, builds, and deploys advanced machine learning and statistical models using the Google Cloud Platform. This role bridges data engineering and business strategy, requiring heavy use of cloud-native AI tools to extract actionable insights and drive product efficiency.
Core Responsibilities
o Model Development: Design, train, and validate predictive, prescriptive, and generative AI models for real-world business use cases.
o GCP Architecture: Architect and optimize ML workflows and data pipelines using core GCP tools like Vertex AI, BigQuery, Dataflow, and Cloud Composer.
o Data Pipelines: Define and integrate data sources, handling data cleansing, transformation, and enrichment for feeding models.
o Stakeholder Communication: Translate ambiguous business problems into mathematical models and present findings to executive or non-technical stakeholders.
o Monitoring & Maintenance: Track model KPIs, evaluate model drift, and ensure continuous validation and retraining.
Required Skills & Qualifications
o Education: Master’s or PhD degree in Computer Science, Statistics, Applied Math, or a related quantitative discipline.
o Programming Languages: Advanced proficiency in Python, R, and SQL.
o GCP & Cloud Tools: Hands-on experience with Google Cloud Platform ecosystem services, specifically Vertex AI, BigQuery/BigQuery ML, Dataproc, and Cloud Storage.
o Machine Learning & Stats: Deep knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn), natural language processing (NLP), and statistical techniques (hypothesis testing, causal inference).
o Generative AI: Familiarity with deploying multimodal models and multi-agent frameworks.
Common GCP Tools Used
o Vertex AI: Google’s unified platform for training, deploying, and managing ML models.
o BigQuery & BigQuery ML: Serverless enterprise data warehouses that allow users to train ML models using standard SQL queries.
o Dataflow & Cloud Composer: Managed services for stream/batch processing and workflow orchestration
To apply for this job email your details to praveenn@cloudraninc.com