Lead Data Scientist - AI & Machine Learning
Tasks
- Build RAG systems
- Build generative AI solutions
- Collaborate with software engineering teams
- Conduct knowledge transfer sessions
- Deploy machine learning models
- Detect concept drift
- Develop predictive models
- Develop prescriptive models
- Ensure scalability and reliability
- Evaluate machine learning models
- Extract insights from data
- Implement agentic applications
- Improve deployed models
- Lead technical discussions
- Mentor junior data scientists
- Monitor model performance
- Productionize AI applications
- Support client AI engagements
Perks/Benefits
- Career advancement opportunities
- Employee parking
- Employee referral program
- English language development courses
- Events
- Flexible work schedules
- Interest-free loans
- Learning time
- Medical insurance
- Planned overtime program
- Social insurance
- Sponsored lunch
- Technical development courses
- Travel and onsite work opportunity
Skills/Tech-stack
AI Search | AWS | AWS SageMaker | Artificial Intelligence | Autogen | Azure | Azure AI | Azure AI Search | Azure ML | CI/CD | Chroma | Concept drift | Concept drift detection | CrewAI | Deep learning | Drift Detection | Embeddings | Experiment tracking | FastAPI | Feature Engineering | Fine Tuning | GCP | Google Vertex | Google Vertex AI | Keras | Langchain | Langgraph | Llamaindex | LoRA | MLOps | MLflow | Machine Learning | Milvus | Model Evaluation | Model versioning | Monitoring | Observability | Pinecone | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | Semantic Search | Statistics | Streamlit | TensorFlow | Vector Databases | Vertex AI | Weaviate
Education
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