Wiser Solutions, Inc.

Machine Learning Engineer

• 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

Principal Machine Learning Engineer

• 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
• 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
• 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

• 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
• 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
• 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

Staff Machine Learning Engineer

Full-stack Engineer

• Think like our users and stakeholders - partner with product, data, and engineering leaders to design intuitive solutions for complex matching and identity problems
• Design and build backend services that support real-time and batch matching workflows
• Develop and maintain user-facing web interfaces that enable inspection, investigation, and human-in-the-loop workflows
• Build high-performance, scalable systems by writing testable, maintainable, and efficient code
• Collaborate across disciplines (ML, data, platform) to integrate matching logic, analytics, and tooling
• Ensure systems are observable, reliable, and secure through thoughtful design and operational best practices
• Own features end-to-end - from initial design through production deployment and iteration
• Continuously improve code quality, architecture, and developer experience
• Contribute ideas and technical direction that influence the evolution of the Matching platform

Senior Software Engineer

Account Executive

• Own the full sales cycle: lead generation, prospecting, engagement, proposal development, negotiation and deal closure.
• Actively build and manage a strong sales funnel, using structured outbound approaches and sales tools (e.g. LinkedIn Sales Navigator, CRM, lead qualification tools).
• Proactively reach, engage and re-engage prospects with a strong bias toward action and follow-through.
• Collaborate with retailers and FMCG manufacturers to identify in-store execution challenges and position Wiser as a strategic partner.
• Demonstrate strong understanding of in-store FMCG dynamics, including: Category management principles, Key selling periods (seasonality, promotions, peak trading moments), Core FMCG and retail KPIs (distribution, visibility, pricing, execution, compliance, availability).
• Confidently discuss in-store performance metrics and execution levers with senior commercial, category and sales leaders.
• Build clear, data-driven commercial proposals, including: Analytical thinking around coverage, targets, scope and expected outcomes, Structuring offers that are realistic, credible and value-driven.
• Support the creation of client insight presentations, leveraging data to highlight opportunities, risks and performance gaps.
• Proactively source, analyze and interpret data to generate relevant insights for prospects and customers.
• Translate complex data into clear commercial narratives that support decision-making.
• Contribute to content creation (sales decks, thought leadership snippets, insight summaries) to support prospect engagement.
• Use insights, data and market knowledge as a lever to spark conversations and maintain engagement with senior stakeholders.

Account Executive – Retail, FMCG

• Develop microservices and web applications for data collection and matching processes
• Collaborate with teams to drive execution and innovation within product suites
• Use domain driven design, event sourcing, and other patterns to enhance system capabilities
• Communicate effectively with the team and executives about project milestones

Lead Software Engineer

• Develop microservices and web applications for data collection and matching processes
• Drive execution and innovation within online retail/brand execution suite
• Develop the next generation consolidated Matching platform capable of handling over 200 million transactions per day
• Introduce domain driven design, event sourcing, CQRS, and other patterns

Staff Software Engineer

• Own the full sales cycle: lead generation, prospecting, engagement, proposal development, negotiation and deal closure.
• Actively build and manage a strong sales funnel, using structured outbound approaches and sales tools (e.g. LinkedIn Sales Navigator, CRM, lead qualification tools).
• Proactively reach, engage and re-engage prospects with a strong bias toward action and follow-through.
• Collaborate with retailers and FMCG manufacturers to identify in-store execution challenges and position Wiser as a strategic partner.
• Demonstrate strong understanding of in-store FMCG dynamics, including:
• o Category management principles
• o Key selling periods (seasonality, promotions, peak trading moments)
• o Core FMCG and retail KPIs (distribution, visibility, pricing, execution, compliance, availability).
• Confidently discuss in-store performance metrics and execution levers with senior commercial, category and sales leaders.
• Build clear, data-driven commercial proposals, including:
• o Analytical thinking around coverage, targets, scope and expected outcomes
• o Structuring offers that are realistic, credible and value-driven.
• Support the creation of client insight presentations, leveraging data to highlight opportunities, risks and performance gaps.
• Proactively source, analyze and interpret data to generate relevant insights for prospects and customers.
• Translate complex data into clear commercial narratives that support decision-making.
• Contribute to content creation (sales decks, thought leadership snippets, insight summaries) to support prospect engagement.
• Use insights, data and market knowledge as a lever to spark conversations and maintain engagement with senior stakeholders.