Data Scientist
Listed on 2026-09-10
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Scientist
Position :
Data Scientist
Location :
Bellevue, WA (Hybrid)
Job Description:
We are seeking a highly skilled AI Engineer Data Scientist with 5 to 7 years of experience in designing developing and deploying AIML solutions The ideal candidate will have strong expertise in Generative AI Large Language Models LLMs Retrieval Augmented Generation RAG Machine Learning and cloud based AI platforms This role involves working closely with business stakeholders data engineers and application teams to develop intelligent scalable and production ready AI solutions that solve realworld business problems
Key Responsibilities
AI Machine Learning Development
- Design develop train and deploy machine learning and deep learning models for business use cases
- Build and optimize predictive classification recommendation NLP and generative AI solutions
- Perform feature engineering model selection hyperparameter tuning and model evaluation
- Analyze structured and unstructured data to generate actionable insights
Generative AI LLM Solutions
- Develop enterprise grade GenAI applications using Azure OpenAI OpenAI or equivalent LLM platforms
- Design and implement Retrieval Augmented Generation RAG pipelines including document ingestion chunking embeddings vector search and retrieval optimization
- Engineer prompts and develop agent based workflows using frameworks such as Lang Chain Lang Graph Semantic Kernel or Auto Gen
- Evaluate model performance for accuracy relevance latency safety and cost efficiency
Data Engineering Solution Development
- Collaborate with data engineers to build scalable data pipelines and AI workflows
- Work with structured and unstructured data sources including databases APIs documents and knowledge repositories
- Develop reusable AI components APIs and microservices for enterprise applications
- Integrate AI solutions into business applications and enterprise platforms
MLOps LLMOps Deployment
- Deploy AIML solutions using Azure ML Azure AI Foundry Databricks or equivalent platforms
- Implement CICD pipelines using Azure Dev Ops or Git Hub Actions
- Monitor model performance manage retraining workflows and address model drift
- Utilize containerization technologies such as Docker and Kubernetes for scalable deployments
- Optimize infrastructure utilization inference performance and LLM token consumption
Responsible AI Security Governance
- Apply Responsible AI principles including fairness transparency explainability and safety
- Implement security controls RBAC data privacy measures and compliance requirements
- Ensure AI applications meet enterprise governance and regulatory standards
- Support monitoring auditing and operational excellence for AI solutions
Required Qualifications
- Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence Engineering or a related field
- 5 to 7 years of experience in Data Science Machine Learning AI Engineering or related disciplines
- Handson experience building and deploying production grade AIML solutions
- Strong experience with Python SQL and machine learning libraries such as Scikitlearn Tensor Flow or Py Torch
- Proven experience with Generative AI LLMs prompt engineering and RAG architectures
- Experience with Azure AI Services Azure OpenAI Azure ML Azure AI Search Databricks or equivalent cloud AI platforms
- Strong understanding of model deployment monitoring MLOps and software engineering best practices
- Experience with vector databases and semantic search technologies
- Familiarity with Docker Kubernetes Git and CICD pipelines
- Strong analytical problem solving and communication skills
Preferred Nice to Have
- Experience with Microsoft Fabric Databricks PySpark Copilot Studio or Azure AI Foundry
- Experience building AI agents multiagent systems and workflow automation solutions
- Knowledge of GraphRAG knowledge graphs evaluation frameworks and document intelligence solutions
- Experience with realtime inference streaming data pipelines and enterprise scale AI deployments
- Azure certifications such as AI Engineer Associate AI102 Azure Data Scientist Associate DP100 or Azure Fundamentals AI900
Skills
Mandatory Skills :
Build AI Agents using Microsoft Agent & Semantic Kernel & Langchain Framework, GenAI - LLMOps, Generative AI on Azure, MLOPS, RAGAS (Retrieval Augumented Generation Assessment) Framework
Good to Have Skills : Azure Open AI Service, Responsible AI
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