Machine Learning Lead
Tasks
- Assess ROI and feasibility for ML solutions
- Build and maintain ML pipelines
- Conduct exploratory workshops with business stakeholders
- Deploy and monitor machine learning models
- Ensure scalable and secure ML infrastructure
- Fine-tune and optimize LLMs
- Ingest preprocess and train ML data
- Integrate ML models into business applications
- Optimize model performance and experimentation
- Translate business needs into ML problem statements
Perks/Benefits
- Accident insurance
- Additional paid time off
- Cafeteria
- Flexible schedule
- Health insurance
- Hybrid work
- Life insurance
- LinkedIn Learning access
- Recognition programs
- Working from home
Skills/Tech-stack
AWS SageMaker | Airflow | Amazon Redshift | Azure Machine Learning | BigQuery | Data Warehousing | Databricks | Deep learning | Docker | Faiss | FastAPI | Flask | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | GraphQL | Hugging Face | Kubeflow | Kubernetes | LLM | MLOps | MLflow | Machine Learning | Milvus | Pinecone | Prefect | PyTorch | REST API | SQL | Scikit-learn | Snowflake | Spark | TensorFlow | Vector Databases | Vertex AI | Weaviate | Weights and Biases | XGBoost
Education
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