AI/ML Engineer
Posted 8 Oct 2026
Advertised as “Senior AI/ML Engineer - R01572485”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- R01572485
- Expected experience
- 6+ yrs
- Management level
- Individual contributor
No salary listed for this role.
CertificationsTensorFlow Developer Certificate, Microsoft Certified: Azure AI Engineer Associate, SAS Certified Specialist, IBM Data Science Professional Certificate
Field of studyComputer Science, Data Science, Mathematics, Statistics (or related)
Study levelBachelor's
Senior AI/ML Engineer
Job requirements
Experience Range: with at least 6 years of experience in AI/ML engineering, including hands-on expertise in designing, building, and operationalizing enterprise-scale AI platforms Key Responsibilities:- Lead the design and architecture of enterprise-scale AI platforms, ensuring scalability, security, and operational readiness
- Define and implement frameworks for model lifecycle management, MLOps/LLMOps, and AI observability to support robust deployment and monitoring
- Establish and enforce Responsible AI principles, governance frameworks, and technical guardrails across AI solutions
- Drive platform-level technical decision-making and define reusable architecture patterns, standards, and reference models for AI and GenAI solutions
- Collaborate with business, data, technology, and platform teams to translate AI architecture principles into production-ready capabilities
- Evaluate emerging AI technologies and assess their applicability to enterprise AI platforms, supporting long-term scalability and business outcomes
- Maintain and improve AI model governance, version control, and documentation for ongoing operational excellence Required Skills:- Expertise in enterprise-scale AI platform design and operationalization
- Deep proficiency in model lifecycle management, MLOps/LLMOps, and AI observability
- Advanced programming skills in Python and PySpark
- Experience with cloud-based AI platforms and modern data/AI architectures
- Knowledge of Responsible AI, AI governance, model risk, security, and compliance
- Hands-on experience with KubeFlow and BentoML for ML pipeline orchestration
- Competence in classification algorithms such as decision trees and SVM
- Experience with Great Expectations and Evidently AI for model validation
- Strong proficiency in regression analysis (linear and logistic)
- Statistical analysis and computing for large datasets Preferred Skills:- Experience with GenAI architectures, large language models, and AI agents
- Proficiency in advanced ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
- Knowledge of vector databases and AI orchestration
- Understanding of AI observability and Responsible AI frameworks
- Experience developing reusable AI architecture patterns and accelerators Desired Qualifications:- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline