Machine Learning/ AI Engineer
Tasks
- Architect LLM and RAG features
- Build adaptive learning and personalized recommendations
- Build agentic AI systems
- Build multi-agent workflows
- Collaborate with data engineers and product managers
- Deploy ML models with SageMaker
- Design agent orchestration and tool use
- Develop online inference and monitoring
- Develop prompt engineering strategies
- Implement ML feature engineering and training pipelines
- Integrate MLFlow for experiments
- Run evaluation pipelines
- Use Airflow for experiment orchestration
Perks/Benefits
- Flexible working hours
- Free Lunches
- Free breakfast
- Free fruit
- Free snacks
- Hybrid work model
- Maternity leave
- Paternity leave
- Personal training budget
- Private health insurance
- Social activities
Skills/Tech-stack
A/B | A/B Testing | APIs | AWS Lambda | Amazon S3 | Amazon SageMaker | Apache Airflow | B testing | Feature Engineering | Graph Databases | LLM | Langchain | Langgraph | MLflow | Machine Learning | Microservices | Monitoring | NLP | Neo4j | Online Inference | Prompt engineering | Python | Recommendation Systems | Retrieval-Augmented Generation | SQL | Training pipelines | Vector Stores
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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