Overview
On Site
Depends on Experience
Contract - W2
Contract - 1 Year(s)
Skills
C# developer
AI/ML
Job Details
Position: C# developer with AI/ML
Location: Redmond, WA
Key Responsibilities
Required Qualifications
Preferred Qualifications
Location: Redmond, WA
Key Responsibilities
- Design, develop, and maintain full-stack solutions using C#, .NET Core, React, and Python/AI-driven components.
- Build automation and orchestration solutions to improve incident response, reliability, and operational efficiency.
- Develop REST APIs, microservices, and backend services to support automation workflows.
- Implement AI/ML models for classification, anomaly detection, predictive analysis, and automated decisioning.
- Integrate automation frameworks and tools with internal systems and cloud services.
- Collaborate with cross-functional teams including DevOps, Security, and SRE to identify automation opportunities.
- Ensure high-quality code, testing, documentation, and adherence to best practices.
- Contribute to architectural decisions, scalability plans, and technical strategy.
- Troubleshoot production issues and participate in on-call support as needed.
Required Qualifications
- 10+ years of experience in the IT field with strong engineering fundamentals.
- Strong, in-depth experience with C#/.NET including .NET Core, APIs, and microservices.
- Strong experience in AI/ML, including model development, training, evaluation, deployment, and integration.
- 7+ years of experience as a Full Stack Engineer, building large-scale applications.
- Proficiency with React, JavaScript/TypeScript, and modern front-end development patterns.
- Experience with Python, especially for AI/ML or automation use cases.
- Hands-on experience building automation or incident response systems (preferred).
- Strong understanding of distributed systems, API design, and cloud-native architecture.
Preferred Qualifications
- Experience with Microsoft Azure, including Azure Functions, App Services, Azure ML, or Cognitive Services.
- Knowledge of DevOps tools, CI/CD pipelines, containerization (Docker/Kubernetes).
- Experience with security, logging, monitoring, and observability technologies.
- Familiarity with MLOps practices and AI deployment pipelines.
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