• Define and evolve Wiser's AI and data science technical strategy in partnership with product and business leadership • Represent Wiser's AI capabilities to customers, partners, and advisors—articulating our approach, roadmap, and differentiation • Identify high-impact opportunities where AI can solve customer problems or create competitive advantage • Establish technical standards, patterns, and best practices that influence engineering decisions across the organization • Architect and build production AI systems including LLM applications, RAG pipelines, semantic search, and traditional ML models • Design rigorous evaluation frameworks, experimentation methodologies, and monitoring systems that ensure AI solutions deliver reliable, measurable results • Own technical quality for AI systems end-to-end: from data pipelines through model deployment to production observability • Partner with product management to translate business requirements into technical approaches and validate solutions against customer needs • Mentor and elevate the AI/data science team (3-5 engineers), raising the technical bar through code review, architecture guidance, and knowledge transfer • Collaborate across engineering teams to integrate AI capabilities into Wiser's broader platform architecture • Drive build-vs-buy decisions and vendor evaluations for AI infrastructure and tooling • Champion AI-native development practices across Wiser engineering—demonstrating how AI tools accelerate development, improve code quality, and change what's possible

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description If you’re a recent college graduate looking for more than a traditional “starter job,” this is your opportunity to build a meaningful career from day one. At AO Globe Life, we combine mission-driven work with professional growth in a remote-first environment designed for performance, mentorship, and long-term opportunity. In this role, you will connect virtually with individuals and families who have requested information about supplemental benefits. Your responsibility is to guide them through their options with clarity, professionalism, and empathy—helping them make informed decisions that protect their financial future. What You’ll Do - Conduct scheduled Zoom consultations with clients - Learn to assess individual needs and present tailored benefit options - Guide clients through the enrollment process with care and attention to detail - Maintain organized, compliant digital records - Participate in weekly team trainings and professional development sessions Qualifications - Enjoy building relationships and communicating with confidence - Thrive in flexible, independent work environments - Are interested in developing business, client service, or advisory skills - Are comfortable using Zoom, CRM systems, and digital collaboration tools - Have a strong work ethic and a growth-oriented mindset Requirements - Authorized to work in the United States - Reliable high-speed internet connection - Windows-based laptop or PC with webcam Benefits - Gain real-world experience in communication, client advising, and consultative business practices - Develop professional confidence through structured training and mentorship - Access performance-based income opportunities with bonus potential - Grow through merit-based advancement pathways into leadership roles - Join a team culture centered on mentorship, collaboration, and purpose-driven impact Company Description For more than 70 years, AO Globe Life has provided supplemental benefits to working-class families nationwide, including union members, credit union members, and veterans. As a remote-first organization, we are committed to building meaningful careers that combine flexibility, professional development, and real impact. If you are ready to launch a career where purpose meets opportunity, apply today.

Position Summary We’re hiring a Senior MLOps Engineer with deep machine learning engineering experience to build and operate the production platform powering ML/LLM-driven healthcare workflows. You’ll design reliable, secure, and compliant systems for model development, evaluation, deployment, monitoring, and continuous improvement—working closely with ML, data, security, and product teams. This role is ideal for someone who has shipped ML systems in production and is excited about LLM orchestration, RAG, evaluations, guardrails, and observability in a regulated environment. Key responsibilities MLOps & ML Platform - Design and operate ML platforms that support end-to-end workflows: data ingestion, feature engineering, training, evaluation, deployment, and monitoring. - Build and maintain CI/CD for ML (testing, packaging, versioning, reproducibility, automated rollbacks, approvals). - Implement MLOps best practices: model registry, experiment tracking, lineage, governance, and reproducible training environments. - Develop scalable training infrastructure (distributed training, GPU scheduling, cost controls, auto-scaling). - Create and maintain feature pipelines / feature stores, ensuring consistency between training and inference (training-serving skew prevention). - Establish model monitoring and observability: performance, drift, bias/fairness signals (where relevant), latency, throughput, and data quality. - Build and own end-to-end LLM delivery pipelines: prompt/versioning, retrieval, orchestration, evaluation, deployment, monitoring, and iterative improvement. - Create robust LLM evaluation harnesses (offline + online): golden datasets, automated regression testing, human-in-the-loop review workflows, and risk scoring. - Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. Deployment, reliability, and operations - Productionize ML Models on GCP using containers and orchestration (e.g., GKE, Cloud Run), and build CI/CD for ML/LLM systems with automated tests and safe rollouts. - Implement observability: tracing, metrics, logs, dashboards, alerting for model/system health (latency, token usage, error rates, retrieval quality, hallucination indicators, drift where relevant). - Build cost controls: token/cost budgeting, caching strategies, autoscaling, and performance tuning. Data, governance, and compliance (Healthcare) - Design systems with security and privacy by default: IAM, least privilege, secrets management, audit logs, encryption, data retention, and PHI/PII handling. - Implement governance: model/prompt lineage, dataset provenance, evaluation traceability, and approval workflows aligned with healthcare compliance expectations. Integrate guardrails: content filters, policy checks, prompt injection defenses, structured output validation, and fallback strategies.

Company Description Wiser Solutions is a suite of in-store and eCommerce intelligence and execution tools. We're on a mission to enable brands, retailers, and retail channel partners to gather intelligence and automate actions to optimize pricing, marketing, and operations initiatives, both in-store and online. Our Commerce Execution Suite is available globally. Job Description LOCATION: This position can be based anywhere in Canada, with a preference for someone in the eastern or central time zone who can work with our teams in the US, Europe and India. ABOUT THE ROLE Wiser Solutions is seeking a Principal Machine Learning Engineer to shape and execute our AI and data science strategy. This is a senior technical leadership role for someone who combines deep expertise in machine learning, data science, and production engineering with the business acumen to translate complex capabilities into customer value. You will be the technical authority for AI at Wiser: defining architectural direction, representing our capabilities to customers and partners, and delivering production systems that drive measurable business outcomes. This role requires someone who operates fluidly between strategic planning and hands-on implementation, who can present to executives and debug production pipelines in the same week. We're building an AI-native engineering culture at Wiser, one where AI tools and techniques are woven into how we work, not just what we build. We need a Principal AI Engineer who doesn't just deliver AI products but models AI-augmented ways of working and helps the broader engineering organization adopt them. If you believe AI is fundamentally transforming software development and you're already living that transformation daily, we want to talk. What You Will Do Strategic Leadership - Define and evolve Wiser's AI and data science technical strategy in partnership with product and business leadership - Represent Wiser's AI capabilities to customers, partners, and advisors—articulating our approach, roadmap, and differentiation - Identify high-impact opportunities where AI can solve customer problems or create competitive advantage - Establish technical standards, patterns, and best practices that influence engineering decisions across the organization Technical Execution - Architect and build production AI systems including LLM applications, RAG pipelines, semantic search, and traditional ML models - Design rigorous evaluation frameworks, experimentation methodologies, and monitoring systems that ensure AI solutions deliver reliable, measurable results - Bridge classical data science approaches (statistical modeling, experimentation design, feature engineering) with modern generative AI techniques - Own technical quality for AI systems end-to-end: from data pipelines through model deployment to production observability Cross-Functional Impact - Partner with product management to translate business requirements into technical approaches and validate solutions against customer needs - Mentor and elevate the AI/data science team (3-5 engineers), raising the technical bar through code review, architecture guidance, and knowledge transfer - Collaborate across engineering teams to integrate AI capabilities into Wiser's broader platform architecture - Drive build-vs-buy decisions and vendor evaluations for AI infrastructure and tooling - Champion AI-native development practices across Wiser engineering—demonstrating how AI tools accelerate development, improve code quality, and change what's possible - Help build an engineering culture where AI augmentation is the default, not the exception Qualifications - 15+ years of experience in data science, machine learning, or ML engineering, with demonstrated progression into technical leadership - Deep expertise in statistical methods, experimental design, and classical ML (not just LLM integration) - Proven ability to architect and deliver production ML/AI systems at scale on cloud platforms (AWS strongly preferred) - Strong software engineering fundamentals: you write production-quality code, not just notebooks - Track record of organization-wide technical influence—setting standards, driving architectural decisions, mentoring engineers - Experience communicating technical strategy and capabilities to non-technical stakeholders, including customers and executives - Demonstrated ability to operate autonomously, identify high-impact problems, and drive initiatives without close direction - Active, daily use of AI coding assistants (Cursor, Claude Code, GitHub Copilot) and a demonstrated belief that AI fundamentally changes how software gets built Technical Depth Expected: - NLP and text analytics: embeddings, semantic similarity, classification, entity extraction, and information retrieval - LLM integration patterns: prompt engineering, RAG architectures, agent frameworks, evaluation methods - Data engineering: pipeline design, data quality, feature stores, and working with large-scale datasets - MLOps: model deployment, monitoring, A/B testing infrastructure, and production observability - Python ecosystem mastery; SQL fluency; comfort with distributed systems concepts Preferred: - Experience with transformer architectures, fine-tuning, or training custom models - Background in retail, e-commerce, or product data domains - Familiarity with LLM orchestration frameworks (LangChain, LlamaIndex) and vector databases - Track record of introducing AI-augmented workflows to teams or organizations - Opinions (and evidence) on how AI changes engineering practices, team structures, or development processes What Success Looks Like First 90 Days: Deep understanding of Wiser's data assets, current AI capabilities, and customer use cases. Identified 2-3 high-impact technical opportunities. Established credibility with the team through hands-on contribution and technical guidance. First 6 Months: Delivered at least one significant AI capability to production with measurable customer impact. Documented and socialized architectural standards for AI development. Shaped our AI roadmap based on customer needs and technical opportunity. Supervisory Responsibility: None Additional Information Other Duties This position may require being on call rotation to address critical production application issues outside of normal working hours. Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice. EEO STATEMENT - Wiser Solutions, Inc. is an Equal Opportunity Employer and prohibits Discrimination, Harassment, and Retaliation of any kind. Wiser Solutions, Inc. is committed to the principle of equal employment opportunity for all employees and applicants, providing a work environment free of discrimination, harassment, and retaliation. All employment decisions at Wiser Solutions, Inc. are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, national origin, family or parental status, disability, genetics, age, sexual orientation, veteran status, or any other status protected by the state, federal, or local law. Wiser Solutions, Inc. will not tolerate discrimination, harassment, or retaliation based on any of these characteristics. Base pay is one part of our total compensation package. Pay is established on an individual basis after considering multiple factors such as relevant experience, education, and other qualifications. In addition, we take into account geographical differentials and make sure pay is equitable with our current staff. For this position, our hiring range for base annual pay is estimated to be USD$155,000 to $170,000, at the time of this posting. Performance-based discretionary bonuses and variable pay plans are available for some positions. If you require accommodation to complete any part of the application process or need an alternative manner to apply, please contact us at [email protected] or call (855) 469-4737. " #LI-Remote - Department: Engineering