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

• Construir la infraestructura de Machine Learning y MLops que permite a Data Scientists desarrollar, desplegar y mantener modelos de Machine Learning en producción • Realizar análisis de datos ad hoc y presentar hallazgos accionables al equipo. • Implementar y mantener monitoreo y alertas sobre indicadores críticos. • Desarrollar e implementar dashboards que permitan optimizar métricas clave. • Colaborar dentro del squad en el diseño e implementación de soluciones analíticas que respondan a las necesidades del negocio. • Traducir requerimientos del squad en modelos de datos y transformaciones dentro del data warehouse. • Coordinar con Data Engineering y otros squads para asegurar la calidad, consistencia y disponibilidad de los datos.

Description Sprout Social empowers businesses worldwide to harness the immense power and opportunity of social media in today’s digital-first world. Processing over one billion social messages daily, our platform serves up essential insights and actionable information to over 30,000 brands, informing strategic decisions that drive business growth and innovation, and fostering deeper, authentic connections to their end customers. Our full suite of social media management solutions includes comprehensive publishing and engagement functionality, customer care solutions, influencer marketing, connected workflows, and business intelligence. We're actively weaving AI throughout our products to drive our business’s growth trajectory. What you’ll do - Build and maintain infrastructure using AWS, Terraform, and Kubernetes to support AI/ML at scale, including Generative AI applications. - Manage the end-to-end lifecycle of machine learning models, ensuring observability and tooling support both scale and speed. - Execute at scale while staying nimble enough to keep up with new capabilities being offered by social network APIs. - Improve processes and champion ideas that matter while holding the team accountable to high code quality and engineering standards. - Support our AI/ML Scientists by developing tooling to streamline model development and deployment. What you’ll bring We’re looking for a creative, collaborative, pragmatic, highly motivated, and impact oriented technical leader to join our team in building great software. If you can solve hard problems, deliver quality server-side software, and confidently guide your peers to learn from and teach each other, we’d love to talk with you! The minimum qualifications for this role include: - 5+ years of experience developing and supporting AI/ML software in a production environment. - 5+ years of experience programming in object-oriented languages such as Java, Python, or C++. - Impact-oriented mindset with an interest in stability at scale and a willingness to engage in feature development. Preferred qualifications for this role include experience: - 3+ years of experience developing and supporting scalable, distributed backend services. - 3+ years of experience building and supporting GPU-heavy services. - 1+ years of experience with LLMs / Generative AI, including managing their unique costs, constraints, and observability challenges. - 1+ years of experience with Infrastructure-as-Code (Terraform) and container orchestration (Kubernetes) within AWS environments. How you’ll grow Within 1 month, you’ll plant your roots, including: - Complete Sprout’s New Hire training program alongside other new Sprout team members. - Get acclimated to the team's current Mission, Goals, and Objectives along with future product roadmaps. - Become familiar with the team’s existing deployment patterns and the ML Ops tooling ecosystem. Within 3 months, you’ll start hitting your stride by: - Decomposing work into small, similarly sized units and working with your squad to prioritize quarterly team goals. - Setting up initial software for model deployment and monitoring of ML models. Partnering with the Infrastructure team to deploy an existing ML model in Kubernetes. Acting as the domain owner for new projects and writing necessary design documents. Within 6 months, you’ll be making a clear impact through: - Rolling out monitoring and alerting tools to identify problems before they affect users. - Helping deploy new ML models processing hundreds of millions of messages a day. - Identifying technical debt and performance bottlenecks, and executing plans to improve the code. - Collaborating effectively across the organization to ensure big-picture alignment. Within 12 months, you’ll make this role your own by: - Becoming the go-to expert of ML Ops at Sprout. - Developing repeatable deployment patterns for data scientists to train, deploy, and evaluate batch, REST, and event-based ML services. - Owning cross-organizational projects and mentoring junior engineers to help them level up technically. - Surprising us! Use your unique ideas and abilities to change your team in beneficial ways. Our Benefits Program We’re proud to regularly be recognized for our team, product, and culture. We invest in our team with a comprehensive, competitive benefits program: - Comprehensive Health & Wellness: Premium BCBSIL medical, dental (high/low plans), and vision (Eyemed) insurance for you and your eligible dependents. - Premium Mental Health Support: Full, free access to Modern Health for you and your dependents, including coaching, therapy sessions, and digital wellness resources. - Retirement Savings: 401(k) plan with a 50% company match on your first 6% of contributions (a 3% total match). - Financial Security: 100% employer-paid Life and Disability insurance for your peace of mind. - Flexible Paid Time Off: A flexible PTO policy, supplemented with additional company-wide Rest & Recharge days throughout the year. - Paid Parental Leave: Up to 16 weeks of paid leave for new parents to support you in expanding your family. - Annual Lifestyle Stipend: A $1,000 USD annual Lifestyle Spending Account to spend on your physical, mental, and financial well-being. - Work From Home Support: A one-time $550 USD stipend to set up your home office, plus a monthly $50 USD stipend for internet. - Giving Back: 16 hours of paid volunteer time annually, plus a $100 annual match for your charitable donations. - Additional Financial Perks: Access to pre-tax commuter benefits, subsidized child/eldercare (Care.com), discounted pet insurance (Figo), and no-cost personalized financial wellness support through Your Money Line. *This list is for informational purposes only. Benefit offerings are discretionary and subject to change and do not constitute a contract or guarantee of benefits. Whenever possible, Sprout wants to provide our team with the flexibility to work in the location that makes the most sense for them. Sprout maintains a remote workforce in many places in the United States. However, we are not set up in all states, so please look at the drop-down box in our application to see whether your state is listed. Few roles require an office setting. If your position requires a physical presence in a Sprout office, it will be evident in the job listing and your offer letter. Individual base pay is based on various factors, including whether you’re located in Zone 1 or Zone 2, as well as relevant experience and skills. In the United States, we have two geographic pay zones. For this role, the expected base pay ranges for new hires are: - Zone 1 (New York, California, Washington): $149,300 - $205,260 USD annually - Zone 2 (All other US states): $135,700- $186,560 USD annually The listed ranges represent earning potential in this position. These ranges were determined by a market-based compensation approach; we used data from trusted third-party compensation sources to set equitable, consistent, and competitive ranges. We also evaluate compensation bi-annually, identify any changes in the market and make adjustments to our ranges and existing employee compensation as needed. Base pay is only one element of an employee's total compensation at Sprout. Every Sprout team member has an opportunity to receive restricted stock units (RSUs) under Sprout’s equity plan. Employees (and their dependents) are covered by medical, dental, vision, basic life, accidental death, and dismemberment insurance, and Modern Health (a wellness benefit). Employees are able to enroll in Sprout’s company’s 401k plan, in which Sprout will match 50% of your contributions up to 6% with a maximum contribution. Sprout offers “Flexible Paid Time Off” and ten paid holidays. We have outlined the various components to an employee’s full compensation package here to help you to understand our total rewards package. Sprout Social is proud to be an Equal Opportunity Employer. We do not discriminate based on identity- race, color, religion, national origin or ancestry, sex (including sexual identity), age, physical or mental disability, pregnancy, veteran or military status, unfavorable discharge from military service, genetic information, sexual orientation, marital status, order of protection status, citizenship status, arrest record or expunged or sealed convictions, or any other legally recognized protected basis under federal, state, or local law. Because Sprout Social is a federal contractor, we affirmatively recruit individuals with a disability and protected veterans. Learn more about our commitment to diversity, equity and inclusion in our latest DEI Report. If you require a reasonable accommodation for any part of the interview process or to submit your application, please email us at accommodations@sproutsocial.com. Include the nature of your request and your preferred contact information. We'll do everything we can to support your success during our recruitment process while upholding your privacy. Please note that only inquiries regarding accommodations will receive a response from this email address; other inquiries will not be addressed (e.g., you send your resume but are not requesting an accommodation). For more information about our commitment to equal employment opportunity, please click here (1) Equal Opportunity Employment Poster and (2) Sprout Social's Affirmative Action Statement. Additionally, Sprout Social participates in the E-Verify program in certain locations, as required by law. #LI-REMOTE Sprout Social Inc. and its subsidiaries process personal data submitted through your application to assess your qualifications for employment and to inform our hiring decision and, where applicable, for required governmental reporting. For more information, please review Sprout's Global Applicant Privacy Notice.

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 450 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together? As a Staff Machine Learning Engineer, Personalization you will lead the technical charge to move us from static feeds to a "Cohort-First, Individual-Next" personalization strategy. Your work will directly impact Time-to-Bet and Deposit Velocity by ensuring no user has to scroll endlessly for relevant sports and markets based on their preferences. What you’ll do: - Architect the Hybrid Engine: Design and build the "Project Bridge" architecture, transitioning the platform from heuristic-based logic (Cohort/Geo-based) to fully real-time ML personalization (Vector Search/Neural Networks). - Real-Time Inference at Scale: Steer the design and deployment of low-latency services (Segment Service & User Profile Service) using Redis/DynamoDB to serve personalized board orderings, deposit defaults, and "For You" feeds in milliseconds. - Feature Engineering & Data Strategy: Partner with Data Science to build the logging pipelines that tag why a user saw an item (data labeling). You will create the feature store required to train future neural networks for individual-level personalization. - Solve the "Cold Start" Problem: Implement logic for dynamic league ordering and deposit smart-defaults based on geospatial data and initial user cohorts, ensuring immediate relevance for new users. What you have: - 7+ years of experience in Backend/ML Engineering with a specific focus on Recommendation Systems (RecSys) or Personalization engines in production. - 3+ years of technical leadership, acting as a lead and driving architecture decisions for high-traffic consumer applications. - Experience with Real-Time Data: Proficient in streaming architectures (Kafka/PubSub) and low-latency lookups (Redis, DynamoDB) to serve model inference in <200ms. - MLOps Experience: Experience with the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, or Databricks. - Strong Coding Skills: Expert in Python and SQL; proficiency in Go or Rust is a strong plus for high-performance inference layers. - Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE) or AWS equivalents. What makes you stand out: - Experience implementing "bandit" algorithms or reinforcement learning for content ranking. - Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading. - Experience building "Feature Stores" that bridge batch historical data with real-time event streams. Where you’ll live: - While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks:The typical salary range for this position is $220,000 to $280,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process. This application period will remain open for 30 days. We’re committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting. Date Posted: 2/4/2026 1st Extension: 3/4/2026 Benefits you’ll receive:In addition to your great compensation package, full-time employees will be eligible for the following perks: - Company-subsidized medical, dental, & vision plans - 401(k) plan with company match - Annual bonus - Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!) - Generous paid leave programs, including 16-week paid parental leave and disability benefits - Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked - Company-wide in-person events and team outings - Lifestyle enhancement program - Company equipment provided (Windows & Mac options) - Annual performance reviews with opportunities for growth and career development You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time. PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.