Blend360
Technology
SeniorAIArchitectGenAI&RecommendationSystems
“Senior AI Architect - GenAI & Recommendation Systems at Blend360. Skills: AI Architecture, GenAI, Recommendation Systems, Deep Learning, Transformer Models, MLOps. Define technical investments with business objectives. Mentor AI/ML engineers”
Industry & Context.
Problem framing; Translate ambiguous business problems
What They're Looking For.
Must Have
Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or quantitative field, 10+ years of experience in data science and machine learning, 3–5 years in people management or technical leadership role, Deep, hands-on expertise designing and training custom transformer architectures, Applied data science foundation, Proficiency in Python, Proficiency in core ML/DL libraries, Direct experience with industry datasets in marketing & media OR telecommunications, Command of SQL, Experience with large-scale data platforms, Experience owning end-to-end MLOps, Exceptional executive communication skills
Nice to Have
Ph.D. strongly preferred, Professional services experience, Experience with privacy-preserving ML, Knowledge of graph neural networks (GNNs), Published research or conference contributions, Experience with real-time inference and streaming ML pipelines, Experience building custom transformer models, Deep experience with OpenAI focused on embeddings
What You'll Do.
Define technical investments with business objectives
Mentor AI/ML engineers
Manage AI/ML engineers
Manage senior data scientists
Manage MLOps engineers
Set performance expectations
Foster high-performance culture
Partner with cross-functional leaders
Prioritize initiatives
Measure organizational impact
Establish engineering standards
Establish code review practices
Establish model governance frameworks
Lead design of custom transformer models
Lead development of custom transformer models
Drive innovation in attention mechanisms
Drive innovation in positional encodings
Drive innovation in tokenization strategies
Oversee adaptation of foundation models
Oversee fine-tuning of foundation models
Champion reproducible experimentation
Champion architectural decision documentation
Oversee end-to-end data science workflows
Deploy models to production
Ensure statistical rigor
Guide team in building data pipelines
Lead technical discovery with clients
Lead solutioning with clients
Translate business problems into AI initiatives
Present AI strategy to C-suite
Present model results to C-suite
Present roadmap updates to C-suite
Contribute to business development
Support RFP responses
Lead technical portions of client proposals
Help grow AI engineering practice
Establish production standards for model deployment
Establish production standards for model monitoring
Establish production standards for drift detection
Establish production standards for automated retraining
Drive adoption of MLOps best practices
Implement model governance
Implement explainability
Implement responsible AI standards
How You'll Work.
Team & Collaboration
Cross-functional leaders; AI/ML engineers; Senior data scientists; MLOps engineers; Enterprise clients; C-suite stakeholders
Communication Scope
Executive presentations; Client presentations; Technical strategy; Model results; Roadmap updates
Process & Methodology
Roadmap definition, Resource allocation
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