AI/ML Architect
AI/ML Architect
Recro- Posted 12 hours ago
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Job Description
Experience: 8–10 Years | Role: Individual Contributor | Shift: US Central Time initially
Key Requirements:
- Strong hands-on experience in AI/ML solution design and architecture
- Mandatory: Snowflake + Microsoft/Azure ecosystem
- Integration experience with Salesforce and ServiceNow
- Strong understanding of business problems and translating them into AI/ML solutions
- Experience designing and implementing solutions, not just execution
- Good to have: AWS, Databricks, Computer Vision, Churn/Risk Models
- Exposure to Responsible AI, Model Governance & regulated environments
- Snowflake/Microsoft certifications are a plus
What we're looking for:
Someone who can understand the business problem, select the right technology, design the solution, and remain hands-on while guiding junior engineers.
Not a fit:
Pure Python Developers
Full-Stack/Frontend profiles
Profiles without Snowflake + Microsoft/Azure + Salesforce/ServiceNow experience
More Info
Key Skills
Churn Risk Models
Responsible AI Model Governance
AI ML solution design and architecture
About Company
Skills:
snowflake , Gdpr, Machine Learning, Software Engineering, MLops, Rpa, Technical Architecture, Ai, CCPA
Skills:
Deep Learning, Tensorflow, Pytorch, Computer Vision, Azure ML, Microservices, AWS, Kubernetes, Python, Docker, Apis, Nlp, Airflow, cloud platforms, scalable system design, large-scale systems, AI ML system design and architecture, data engineering pipelines, MLOps tools, Kubeflow, MLflow, Scikit-learn, SageMaker, GCP AI, generative AI
Skills:
Ml, APEX, Flows, Mobile Application Development, Ai, agentic systems architecture, AI governance, Gemini, cloud-native architecture, Agentforce custom agent frameworks, Agentforce, AI agents, LLM-based systems, Lightning Web Components, agentic tool-use patterns, automation platforms, Salesforce Field Service solution development, integration patterns, platform scalability principles, Salesforce platform architecture, prompt engineering, responsible AI, AI risk frameworks, LLM orchestration