Ai/Ml Engineer
Tasks
- Build AI and machine learning solutions in production
- Create model evaluation suites with end users
- Deploy machine learning models across full lifecycle
- Design agentic system architectures
- Develop data pipelines for customer environments
- Implement RAG knowledge assistants in production
- Integrate AI services with cloud environments
- Set up MLOps monitoring and observability
- Translate business requirements into technical solutions
- Version ML models and pipelines
Perks/Benefits
- Additional dental care
- Childcare support
- Company stock purchase plan
- Comprehensive healthcare
- Dental care
- Flexible home office budget
- IT and remote budget
- Laptop and phone benefit
- Lunch benefit
- Massage every month
- Massage service
- Mental health services
- One off home cleaning service
- Public transportation benefit
- Recurring training and learning sessions
- Remote work
- Sports and culture benefit
- Travel and leisure insurance
- Wellbeing hour weekly
- Yearly performance bonus
Skills/Tech-stack
AWS | Agentic Systems | Azure | CI/CD | Cloud platform | DBT | Databricks | Docker | Embeddings | Feature Engineering | Generative AI | Google Cloud | Google Cloud Platform | Langchain | Langgraph | Llamaindex | MLOps | Machine Learning | Model Deployment | Model Monitoring | Model versioning | Observability | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | SQL | Scikit-learn | Snowflake | Supervised Learning | TensorFlow | Unsupervised Learning | Vector Databases
Education
N/A
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