Principal AI Engineer
Sterling, VA, United States
USD 110K-225K (estimate) Senior-level Full Time
Tasks
- Address data quality issues
- Analyze and preprocess data
- Build and optimize ML models using PyTorch, Hugging Face, Scikit-learn, LangChain
- Collaborate on requirements and specifications
- Define architecture for LLMOps/MLOps
- Deploy models in cloud environments with containers, Kubernetes
- Design data pipelines with data engineers
- Design scalable AI/ML solutions
- Develop AI prototypes and PoCs
- Ensure AI solutions meet standards on performance, security, privacy
- Implement unstructured data pipelines with embeddings, vector search, Knowledge Graphs
- Integrate low-code AI features into solutions
- Leverage platforms like Databricks, Snowflake
- Mentor team members on AI/ML best practices
- Monitor and iterate on deployed models
- Stay updated on AI technology advancements
- Support pre-sales and stakeholder communication
- Utilize cloud-native AI services (AWS, Azure, GCP)
Perks/Benefits
Skills/Tech-stack
AI Governance | AI/ML Platforms | Automl | CI/CD | Cloud AI | Cloud AI/ML | Cloud AI/ML platforms | Code platforms | Containers | Data Pipelines | Data Preprocessing | Generative AI | Hugging Face | Knowledge graphs | Kubernetes | Langchain | Low Code | Low-Code Platforms | ML Platforms | MLOps | MLflow | Model Evaluation | PyTorch | Python | RAG Architectures | Scikit-learn | Vector Search
Education
Bachelor's in Computer Science | Data Science | Related Field
Roles
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