AI/ML Engineer
Tasks
- Build CI/CD pipelines
- Create reports and presentations
- Create standard operating procedures
- Deliver data-driven insights
- Develop accelerators and sales assets
- Develop analytical techniques for business opportunities
- Develop model monitoring and retraining workflows
- Drive delivery of analytics solutions
- Establish center of excellence
- Identify data pain points
- Lead data science projects
- Support pre-sales calls
- Train and deploy machine learning models
Perks/Benefits
Skills/Tech-stack
API Development | Automl | BigQuery | CI/CD | Classification | Cloud Functions | Cloud Run | Cloud Storage | Cloud platform | Clustering | Data Analysis | Data Cleansing | Data Science | Data Visualization | Data Warehousing | Deep learning | Docker | Docker deployment | Document AI | ELT | ETL | Ensemble modeling | Exploratory Data Analysis | Feature Engineering | Generative AI | Git | Google Cloud | Google Cloud Platform | Graph Data | Graph Data Science | Keras | Kubernetes | Langchain | Language Models | Large Language Models | Looker | MLOps | Model Evaluation | Model Monitoring | Model Tuning | Model versioning | NoSQL | Prompt engineering | PubSub | PyTorch | Python | Recommendation Systems | Regression | Reinforcement Learning | Relational databases | Responsible AI | Retrieval-Augmented Generation | SQL | Scikit-learn | Series analysis | Shell Scripting | TensorFlow | Time Series | Time Series Analysis | Vector Databases | Vertex AI
Education
N/A
Roles
AI | AI/ML Engineer | Data Scientist | Engineer | ML Engineer | Scientist
Regions
Countries
States
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