Artificial Intelligence/Machine Learning Data Engineer
USD 88K-108K Mid-level Full Time
Tasks
- Apply responsible AI
- Apply safety filters
- Automate deployments
- Build RAG systems
- Build large-scale data pipelines
- Containerize services
- Deploy AI systems securely
- Deploy machine learning models
- Design AI agents
- Detect bias
- Develop AI agents
- Develop machine learning solutions
- Ensure model fairness
- Implement automated testing
- Implement prompt engineering
- Integrate AI agents with enterprise APIs
- Integrate LLMs
- Integrate with microservices
- Integrate with workflow systems
- Manage vector databases
- Operationalize AI agents
- Optimize embeddings
- Orchestrate AI agents
- Orchestrate containers
- Perform code reviews
- Process streaming data
- Set up CI/CD pipelines
Perks/Benefits
Skills/Tech-stack
AWS | Agent Frameworks | Agent Orchestration | Amazon Kinesis | Amazon SageMaker | Apache Kafka | Apache Spark | Autogen | Automated testing | Azure | Azure Event | Azure Event Hubs | Azure Machine Learning | Bias detection | CI/CD | Chroma | Containerization | Databricks | Docker | Embedding Optimization | Enterprise APIs | Event Hubs | Faiss | Function Calling | Go | Google Cloud | Java | Kubeflow | Kubernetes | LLM integration | Langchain | Language Models | Large Language Models | Llamaindex | MLflow | Machine Learning | Microservices | Milvus | Model Fairness | Pinecone | Prompt engineering | PyTorch | Python | RAG | Redis | Responsible AI | Retrieval-Augmented Generation | SQL | Safety filters | Scala | Scikit-learn | Semantic Kernel | Streaming | TensorFlow | Vector Databases
Education
Associate Degree | Bachelor of Engineering | Bachelor of Science
Roles
AI | AI Engineer | Data Engineer | Engineer | Learning Engineer | Machine Learning Engineer
Regions
Countries
States
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