AI/ML Engineer
Tasks
- Apply analytical techniques
- Build accelerators and sales assets
- Create client reports and presentations
- Create standard operating procedures
- Deliver analytics solutions
- Deliver data-driven insights
- Develop and monitor MLOps workflows
- Develop custom and off the shelf models
- Establish AI ML center of excellence
- Identify data pain points
- Serve as technical subject matter expert
- Support pre sales calls and proposals
- Train and deploy machine learning models
Perks/Benefits
Skills/Tech-stack
API Development | BigQuery | CI/CD | Classification | Cloud Functions | Cloud Run | Cloud Storage | Clustering | Data Analysis | Data Cleansing | Data Science | Data Visualization | Data Warehousing | Deep learning | Docker | Document AI | ELT | ETL | Ensemble learning | Exploratory Data Analysis | Feature Engineering | Git | Graph Data | Graph Data Science | Keras | Kubernetes | LLMs | Langchain | Looker | Model Evaluation | Model Monitoring | Model Tuning | Model retraining | Model versioning | NoSQL | Prompt engineering | Pub/Sub | PyTorch | Python | RAG | 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
Roles
AI | AI/ML Engineer | Data Scientist | Engineer | ML Engineer | Scientist
Regions
Countries
States
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