Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Support Experience engineering organization builds and improves Stripe’s user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions. We’re accountable for the quality and reliability of this support stack and we use data and firsthand user research to continuously improve it. 

Providing great support to users of all sizes is culturally important to everyone at Stripe. We are a group of friendly, user-oriented engineers that partner closely with Stripe’s world-class design, product, and operational teams. This includes the external-facing support interfaces (support.stripe.com), content, entry points, internal tooling, case routing, and helping product teams across the company reduce support volume by improving our products. We are also using the latest generative AI technologies to re-imagine support experiences, and are developing AI assistants for Stripe’s users and internally to help our operations teams be more productive.

What you’ll do

As a Machine Learning Engineer on the Support Experience team, you'll play a crucial role in enhancing our self-serve support experiences. You will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production. For example, we apply LLMs to answer user questions with conversational agents and personalize product documentation, and are building automated systems to solve complex user problems. You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products. You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community. 

Responsibilities

• Design  and implement state-of-the-art ML models and large scale ML systems for enhancing self-serve support capabilities, balancing ML principles, domain knowledge, and engineering constraints
• Develop and optimize contextual conversation models and ML-powered resolution flows for common support scenarios, using tools such as PyTorch, TensorFlow, and XGBoost
• Create and refine pipelines for training and evaluating models in both offline and online environments, with a focus on improving support quality and user satisfaction
• Implement ML features that streamline information collection and processing for support agents, enhancing overall support efficiency
• Collaborate with product, strategy, and content teams to propose, prioritize, and implement new AI-driven support features and improve answer capabilities
• Stay current with the latest developments in ML/AI, particularly in natural language processing and conversational AI, and apply innovative ideas to improve support experiences

Who you are

We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions. You have experience developing efficient feature pipelines, building advanced ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment.

Minimum requirements

• Bachelor's Degree in ML/AI or related field (e.g. math, physics, statistics)
• 3+ years in AI/ML and backend engineering, including building and operating production ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Deep and up-to-date applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration architectures, post-training methods, code generation, benchmarks and evaluations, etc. Familiarity with classical ML methods and common frameworks e.g. Pytorch, TensorFlow.
• Proficient in Python; strong distributed systems and data science fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Preferred qualifications

• MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)
• Experience working in Java or Ruby codebases
• Experience designing, deploying, and owning Agentic LLM solutions (e.g., multi-step orchestrators, tool use/function calling) specifically for complex customer support or internal workflow automation.
• Comfortable working with distributed teams across multiple locations and time zones

Role Summary

We’re looking for a Digital Content & AI Automation Manager to lead our transition to 'Vibe Marketing.' Inspired by the shift toward Vibe Coding, we want to bridge the gap between creative intent and digital execution. You’ll move Okta away from manual tickets and rigid CMS forms toward an agentic, self-service model—building the tools that allow marketers to describe a goal in natural language and see it manifest across our digital ecosystem.

This is a test, learn, build, iterate role. You aren't just managing a stack; you’re building an autonomous engine that empowers every marketer to be a creator.

What You’ll Actually Do

• Build the "Vibe Marketing" tools: Create the workflows and agentic layers that allow non-technical stakeholders to manage and scale digital content across its entire lifecycle using natural language and AI assistance.
• Develop Agentic Support Models: Prototype and deploy AI agents that act as "co-pilots" for Marketing Managers—handling everything from automated tagging and metadata to complex distribution across our headless ecosystem.
• Architect Self-Service Systems: Reduce the "time-to-live" by building modular, reusable content structures that agents can manipulate, moving us beyond the constraints of traditional platforms like Adobe Experience Manager.
• Operate Like a Lab: Run rapid experiments with emerging AI tools and automation platforms. Build scrappy prototypes—not just strategy decks—to prove that "vibe-based" creation works at enterprise scale.
• Partner Across Teams: Bridge the gap between "what if" and "here’s how," working with Marketing, Engineering, and Digital teams to turn agentic concepts into production-ready workflows.

What We’re Looking For

• The "Vibe" Mindset: You understand the shift from "doing the work" to "directing the agents." You’ve followed the Vibe Coding movement and are itching to apply it to Marketing Tech.
• 4–8 Years of Experience: You’ve seen the limitations of legacy CMS architectures and are ready to bypass those bottlenecks by building a modern, agent-led content supply chain.
• Hands-on AI & Automation: You don't just prompt; you build. You have experience with APIs, MCP, LLM orchestration, and connecting tools to create seamless loops.
• Technical Fluency: You aren't a full-stack engineer, but you understand how to navigate enterprise complexity—you're comfortable with structured content, and the logic of how data flows between a headless CMS, an LLM, and the front-end.

#LI - Hybrid

P24086_3333054

Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

About the Team

The Global Safety and Security team advances DoorDash through the protection of people, property, operations, brand, and reputation. We manage safety and security risk and provide value across the business through technology, and a people-first approach. Our team strives to always be in front and there for our people anytime, anywhere.

About the Role

The Physical Security Agent, Critical Incident Response Team (CIRT) is responsible for real-time monitoring, triage, and response to incidents that impact DoorDash’s global workforce, assets, and operations. You’ll serve as a front-line responder, analyzing alerts, coordinating response actions, and escalating issues according to established Global Safety & Security (GSS) protocols.

This role sits at the heart of DoorDash’s emergency response network — ensuring rapid, informed, and coordinated action during critical events such as natural disasters, workplace emergencies, or significant disruptions. Working closely with regional and global partners, you’ll help keep DoorDash’s people safe and operations running smoothly around the clock.

Key Responsibilities

Security Operations & Monitoring

• Monitor and assess alerts from global intelligence, safety, and security systems to identify potential threats or incidents
• Patrol and assess potential behavioral escalations or concerns
• Conduct routine lobby and facility patrols to ensure safety, security, and compliance
• Perform door, camera, and access point checks

Access Control & Visitor Management

• Manage employee and guest badging, including badge printing, activation, and access level assignments (experience with Genetec, Lenel S2, or similar systems)

Incident Response & Safety

• Triage incidents, determining severity and escalation requirements in accordance with CIRT standard operating procedures
• Act as the initial point of contact for incident reporting, ensuring information is captured accurately and escalated efficiently
• De-escalate situations involving employees, vendors, and guests as needed
• Support activation and execution of emergency response and crisis communication protocols

Employee Engagement

• Coordinate with internal teams (e.g., Workplace, HR, Legal, Comms, Operations) and external partners (e.g., law enforcement, emergency services) during incident response
• Disseminate timely situational updates and intelligence to relevant stakeholders

Asset & Inventory Management

• Maintain inventory, readiness, and restocking of first aid kits, AEDs, and other emergency response materials in coordination with Workplace teams
• Ensure emergency supplies are documented, tracked, and available to support incident response operations

Documentation, Compliance & Technology

• Maintain SOPs, post orders, incident reports, and audit records
• Ensure adherence to corporate safety, security, and compliance standards
• Maintain detailed logs, case notes, and documentation using Jira and other internal tools
• Participate in after-action reviews to improve process and operational efficiency

Events Support

• Support local events, executive visits, and executive protection details from an incident monitoring, coordination, and escalation perspective
• Coordinate with Workplace, Security, and event stakeholders to ensure appropriate safety coverage and response readiness
• Monitor events for emerging risks, incidents, or escalations and facilitate timely response as needed

Additional Duties

• Support after-hours, weekend, and holiday response as required by business needs
• Support special projects or operational needs as assigned
• Assist with credentialing, crowd flow, and safety monitoring during higher-volume office days or events
• Travel up to 5% as required for training or business support

Schedule & Work Environment

• On-site role, 40 hours per week
• Schedule may vary based on operational needs
• After-hours, weekends, and holidays as required by business needs

About You

• 2–4+ years of experience in emergency management, public safety, dispatch, GSOC, or related security operations environment
• CPR, First Aid, AED certification (current)
• Advanced First Aid training (EMT preferred) 
• Strong analytical and situational awareness skills — able to prioritize under pressure
• Exceptional written and verbal communication, particularly in high-stakes or time-sensitive situations
• Familiarity with incident management systems and communication tools (e.g., Everbridge, Dataminr, OnSolve, or similar)
• Calm and composed in emergencies, with strong problem-solving and judgment skills
• Willingness to work non-standard hours, including nights, weekends, and holidays
• Fluency in English required; additional language skills (Spanish, French, or Mandarin) a plus
• Bachelor’s degree or equivalent work experience in a relevant field (e.g., emergency management, criminal justice, homeland security)
• Great communication and relationship building skills

You’ll Love This Role If

• You thrive in high-tempo, real-time environments where every second matters
• You find purpose in helping protect people and operations from emerging risks
• You enjoy staying calm under pressure and making smart, quick decisions
• You value teamwork, precision, and continuous improvement

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

As a Senior+ Agentic Analytics Engineer at Opendoor, you will join the Data organization and help build something that doesn't exist at most companies: an Agentic Analytics team. This is a high-impact IC role at the intersection of data science, data engineering, and AI.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it.

Why This Role

Most analytics teams are stuck in reactive mode—fielding ad-hoc requests and building dashboards that go stale. We're building something different: AI systems that proactively tell leaders what they should focus on, why it matters, and what to do about it.

If you want to define what analytics looks like in an AI-first company, this is it.

What You'll Do

Build Proactive Intelligence Systems

• Design and deploy AI agents that monitor business performance and surface actionable insights without being asked

• Architect systems that shift analytics from "answering questions" to "anticipating needs"

• Create intelligent alerting that distinguishes signal from noise and recommends specific actions

Create AI-Powered Analytics Tools

• Develop natural language interfaces that let business leaders query data conversationally

• Build semantic layers that translate business concepts into data structures optimized for LLM reasoning

• Ship internal tools that transform how Opendoor makes decisions at every level

Own the Analytics-to-Action Pipeline

• Design data models that support automated analysis, pattern detection, and AI agent interactions

• Build workflows that connect insight generation to recommended actions

• Establish feedback loops that make our AI systems smarter over time

Drive Leverage Across the Business

• Identify high-value opportunities where AI can augment human decision-making

• Implement end-to-end solutions using Claude, custom agents, and modern AI tooling

• Measure impact rigorously—we care about decisions influenced, not dashboards built

We're Looking for Teammates Who Have

Technical Foundation

• 5+ years of experience in analytics, data science, or data engineering, with increasing scope and ownership

• Expert-level SQL with demonstrated ability to design complex data models and optimize for both human and AI consumption

• Strong Python proficiency for data engineering, automation, and AI agent development

• Experience with modern data warehouses (Snowflake, BigQuery, or similar) and the broader data stack (dbt, Airflow, etc.)

AI & Automation Expertise

• Hands-on experience building and deploying AI agents or LLM-powered applications in production

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Proven ability to identify high-ROI automation opportunities and ship end-to-end solutions

Analytics & Business Acumen

• Track record of driving measurable business impact through analytics—not just producing analyses, but influencing decisions

• Strong analytical intuition—you know what questions matter before they're asked

• Experience translating ambiguous, cross-functional business problems into technical solutions

• History of operating autonomously and setting direction, not just executing on defined projects

Leadership & Influence

• Experience mentoring other analysts or engineers, formally or informally

• Demonstrated ability to influence senior stakeholders and drive alignment across teams

• Comfort operating in ambiguity and shaping strategy, not just responding to it

• Track record of building systems and processes that scale beyond yourself

Builder Mindset

• You ship products, not just dashboards 

• You'd rather build something useful in a week than something perfect in a quarter

• You measure success by business impact, not technical complexity

• You're energized by creating leverage—building once so others benefit forever

Bonus Points If You Have

• Experience in real estate, fintech, or marketplace businesses

• Background in marketing analytics, sales operations, product analytics, or pricing/economics

• History of building tools or platforms that replaced recurring analyst work

• Experience leading technical projects or small teams

About the Role:

We are seeking an experienced Principal Software Engineer (Data) to join our fast-paced, collaborative data team. In this role, you will have broad authority to drive the direction of our technographic data services, building world-class data pipelines and systems to process billions of signals and data points. This is an exciting opportunity to solve challenging problems and make a big impact as we invest in making technographics a first-class offering.

What You'll Do:

• Build and optimize big data pipelines to extract and process signals from the web, job postings, and other sources
• Design and implement data architectures and storage solutions to efficiently handle massive data volumes
• Collaborate closely with data scientists to support and integrate ML models into data workflows
• Continuously improve data quality, performance, and scalability of our technographic data platform
• Drive technical strategy and roadmap for the data processing infrastructure.

What We're Looking For:

• Extensive experience building and scaling big data pipelines and architectures from scratch
• Deep expertise in big data frameworks (Hadoop, Spark) and the JVM stack (Java, Scala)
• Strong software engineering fundamentals and ability to write efficient, high-quality code
• Experience with entity recognition and NLP techniques a plus
• Proven track record delivering results and driving projects in a fast-paced environment
• Excellent collaboration and communication skills to work with data scientists, analysts and product teams
• Passion for leveraging huge datasets to power valuable insights.

Ideal Background:

• 10+ years of experience in software engineering roles.
• Experience working with very large datasets and distributed systems
• Familiarity building data pipelines at large tech companies or data-driven organizations
• Bachelor's or advanced degree in Computer Science, Engineering or related technical field.

#LI-SK1

#LI-Remote

With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.

What you’ll do:

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
• Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
• Work in a high-impact environment with quick experimentation and product launches
• Keeping up with industry trends in recommendation systems 

What we’re looking for:

• 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
• End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
• M.S. or PhD in Machine Learning or related areas
• Expertise in scalable realtime systems that process stream data
• Passion for applied ML and the Pinterest product

Nice To Have:

• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement: 

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times per quarter and therefore needs to be in a commutable distance from the Toronto office (85 Richmond St. W).

#LI-REMOTE

POSITION DESCRIPTION  

ROLE: RECRUITER  
TEAM: TALENT  
LOCATION: TORONTO (HYBRID)  

COMPANY OVERVIEW  

Salt is a North American marketing agency that creates connected experiences through creative, digital & media innovation. 

Our mission is to “Earn the World’s Attention” and Salt is built to find, develop, execute, and amplify the ideas that are worthy of our clients’ audiences. We’ve structured our agency to do what’s right for our clients – to connect different perspectives, to work across mediums, and to focus on delivering meaningful, effective results. 

We’re committed to living up to the values in our name. “Salt of The Earth” means we value collaborative, humble, hard-working people here. We’re looking for people who are as smart as they are kind because we believe the right talent and the right culture help us do what’s right for our clients.   
 
ROLE OVERVIEW  
The Recruiter will partner with the Director of Talent to lead full-cycle hiring for Salt XC. From Creatives and Community Managers to Media, Design, and Digital roles, you’ll help source and secure the talent that drives our work forward.  

You’ll be hands-on in every part of the process: finding top candidates, building strong pipelines, and elevating how we show up in the market. You’re a natural relationship builder with a sharp eye for talent and a drive to make things better. You think fast, act with purpose, and bring fresh ideas to every search.  

CORE RESPONSIBILITIES  

Talent Acquisition and Sourcing 

• Run full-cycle recruitment for assigned departments, from intake to offer.
• Build proactive pipelines through research, outreach, referrals, communities, and events.
• Write inclusive, compelling job postings and calibrate success profiles with hiring managers. 

Candidate Experience and Employer Brand 

• Maintain timely, transparent communication with all candidates. 
• Prepare teams for structured, competency-based interviews and close the loop with clear feedback. 
• Support employer brand efforts through events, content, and partnerships that showcase Salt. 

Recruitment Analytics and Optimization 

• Maintain accurate ATS data; keep stages, notes, and statuses current. 
• Track and share funnel metrics such as time-to-fill, source effectiveness, and conversion. 
• Surface insights to improve speed, quality of hire, and process efficiency. 

Strategic Partnership and Stakeholder Influence 

• Consult with hiring managers on role scope, JD language, interview plans, and assessment. 
• Align searches to headcount plans and hiring priorities; set expectations on pace and pipeline health. 
• Communicate progress, risks, and recommendations clearly and proactively. 

Early Talent and Engagement Programs 

• Own outreach and logistics for intern and early-career programs in partnership with People & Culture. 
• Support campus and community engagement; track conversion and retention outcomes. 
• Provide feedback to improve programming, onboarding, and development pathway 

EXPERIENCE & SKILLS   

• 3–5 years recruiting experience, ideally in a creative or integrated agency environment. 
• Full-cycle recruiting proficiency across diverse roles (Creative, Digital, Media, Operations) with evidence of quality hires and manager satisfaction. 
• Sourcing depth using LinkedIn Recruiter, Boolean search, referrals, communities, and events; comfort building proactive pipelines. 
• ATS fluency with disciplined data hygiene and reporting; able to translate funnel data into actionable insights. 
• Stakeholder partnership skills: consultative intake, expectation setting, structured interview planning, and offer negotiation. 
• Candidate experience excellence: clear, timely communication; respectful feedback; advocacy for inclusion. 
• Process rigor: organized, detail-oriented, and consistent in documentation, compliance, and handoffs to onboarding. 
• Communication and influence: strong writing and presentation; able to advise with empathy and objectivity. 
• EDI mindset: curiosity, fairness, and commitment to broadening access and representation. 

PERKS & BENEFITS THAT SET US APART  
We don’t just talk about balance, growth, and culture, we build for it:  

• Work-Life Flexibility: Hybrid setup, up to 28 paid days off & winter holiday shutdowns.
• Comprehensive Coverage: Health, dental, and vision plans, plus Salt Bucks to spend on what matters to you—wellness, RRSPs, or extra time off.  
• Growth-Driven Culture: Dedicated Salt Days, top-tier learning access, and formal leadership development.  
• Celebration-First Mentality: Legendary team trips, seasonal socials, and Salt Swag that reps your squad.  
• Real Rewards: Referral and new business bonuses, exclusive lifestyle perks, and personalized wellness options.  
• Culture of Belonging: DEI programs, active ERGs, and a workplace where every voice counts.  

WHAT WE STAND FOR  

• Salt of the Earth: We lead with humility, honesty, and heart—always.  
• Do What’s Right: No shortcuts. We choose integrity over ease, every time.  
• Earn Your Salt: We roll up our sleeves, chase results, and celebrate the journey.  
• Make Things Better: We’re solution-seekers, always pushing for smarter ways forward.  
• Seek Different Perspectives: Diversity fuels our thinking. Inclusion drives our impact.  

The anticipated annual base salary range for this position is $65,000–$90,000. Individual compensation within this range is determined based on job-related factors such as experience, skills, level of responsibility, internal equity, and business needs. This range represents the expected base salary for this role and does not include other elements of SALT XC’s total rewards program.

About the Role:

The Discovery Search team (Search FX) sits at the intersection of search, evaluation, and personalization shaping how retailers find the products they love. Our mission is to build the most intuitive, intelligent, and delightful discovery experience in wholesale: one that feels less like a search engine and more like a trusted merchant with an encyclopedic knowledge of what's in stock and what will sell.

As a Staff Engineer on the Search FX team, you will be a primary technical architect for our retailer-facing search surfaces. You will own the technical roadmap for search, recommendations, and Gen-AI experiences that drive a meaningful share of marketplace engagement. You will bridge the gap between high-scale infrastructure and world-class UX, helping unify retrieval, ranking, and personalization into a cohesive, high-performance system.

You’re excited about this role because...

• You will own the technical vision: Define the end-to-end architecture for Faire's search and discovery experience, ensuring it is fast, relevant, and deeply personalized.
• You’ll build at the AI frontier: Integrate LLM-powered capabilities, such as natural language search and intelligent query understanding, directly into the product.
• You’ll solve complex scale problems: Help build high-scale, low-latency systems that navigate millions of products while meeting strict industry latency benchmarks.
• You’ll drive cross-functional impact: Partner closely with Data Science, Product, and Design to iterate on ranking models and UX components.
• You’ll be a mentor and leader: Foster a culture of engineering excellence and ownership, upskilling the team on technical expertise and decision-making.

What You'll Do:

• Architect Next-Gen Search: Lead the design of composable grids, intent-aware routing, and orchestration layers that unify retrieval and ranking.
• Modernize Query Understanding: Leverage LLMs to consolidate the QU stack, improving accuracy for long-tail queries and edge cases.
• Optimize Performance: Drive initiatives to increase retrieval candidates (e.g., 10x growth) while maintaining stable search latency.
• Launch AI-Driven Features: Develop systems like "Search Missions" that use offline pipelines and LLMs to recover failed search sessions through expanded queries.
• Bridge AI and UX: Work with client engineers on SDUI and React Server Components to improve performance and developer velocity for dynamic search layouts.
• System Ownership: Take accountability for the reliability and observability of the search funnel, from query planner refactors to real-time retrieval monitoring.

Qualifications:

• Experience: 7+ years of professional software engineering experience, with 3+ years as a technical leader driving complex, cross-team projects.
• Product Sensibility: A strong user-first mindset and the ability to translate ambiguous business problems into clear technical direction.
• AI/ML Familiarity: Experience partnering with Data Science to deploy and leverage machine learning and gen-AI systems in search experiences across ranking and retrieval.
• Domain Expertise: knowledge of search/query processing, including traditional, semantic, and hybrid frameworks (e.g., Elasticsearch, Lucene).
• Technical Stack: Strong programming skills in Kotlin or Java, with experience in high-performance backend systems, Protocol Buffers, and MySQL.
• Strategic Leadership: Demonstrated ability to contribute to team strategy without supervision and influence the broader organizational roadmap.

Technologies We Use and Teach:

• Backend: Kotlin, Java 16, Hibernate, Guice, Jersey
• Search/Data: Elasticsearch, FAISS, Redis, DynamoDB
• Communication: Protocol Buffers, HTTP, JSON
• Infrastructure: AWS, Kubernetes, Buildkite, Datadog

Salary Range:

San Francisco: the pay range for this role is $231,000 - $318,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About the Role:

The Discovery Search team (Search FX) sits at the intersection of search, evaluation, and personalization shaping how retailers find the products they love. Our mission is to build the most intuitive, intelligent, and delightful discovery experience in wholesale: one that feels less like a search engine and more like a trusted merchant with an encyclopedic knowledge of what's in stock and what will sell.

As a Staff Engineer on the Search FX team, you will be a primary technical architect for our retailer-facing search surfaces. You will own the technical roadmap for search, recommendations, and Gen-AI experiences that drive a meaningful share of marketplace engagement. You will bridge the gap between high-scale infrastructure and world-class UX, helping unify retrieval, ranking, and personalization into a cohesive, high-performance system.

You’re excited about this role because...

• You will own the technical vision: Define the end-to-end architecture for Faire's search and discovery experience, ensuring it is fast, relevant, and deeply personalized.
• You’ll build at the AI frontier: Integrate LLM-powered capabilities, such as natural language search and intelligent query understanding, directly into the product.
• You’ll solve complex scale problems: Help build high-scale, low-latency systems that navigate millions of products while meeting strict industry latency benchmarks.
• You’ll drive cross-functional impact: Partner closely with Data Science, Product, and Design to iterate on ranking models and UX components.
• You’ll be a mentor and leader: Foster a culture of engineering excellence and ownership, upskilling the team on technical expertise and decision-making.

What You'll Do:

• Architect Next-Gen Search: Lead the design of composable grids, intent-aware routing, and orchestration layers that unify retrieval and ranking.
• Modernize Query Understanding: Leverage LLMs to consolidate the QU stack, improving accuracy for long-tail queries and edge cases.
• Optimize Performance: Drive initiatives to increase retrieval candidates (e.g., 10x growth) while maintaining stable search latency.
• Launch AI-Driven Features: Develop systems like "Search Missions" that use offline pipelines and LLMs to recover failed search sessions through expanded queries.
• Bridge AI and UX: Work with client engineers on SDUI and React Server Components to improve performance and developer velocity for dynamic search layouts.
• System Ownership: Take accountability for the reliability and observability of the search funnel, from query planner refactors to real-time retrieval monitoring.

Qualifications:

• Experience: 7+ years of professional software engineering experience, with 3+ years as a technical leader driving complex, cross-team projects.
• Product Sensibility: A strong user-first mindset and the ability to translate ambiguous business problems into clear technical direction.
• AI/ML Familiarity: Experience partnering with Data Science to deploy and leverage machine learning and gen-AI systems in search experiences across ranking and retrieval.
• Domain Expertise: knowledge of search/query processing, including traditional, semantic, and hybrid frameworks (e.g., Elasticsearch, Lucene).
• Technical Stack: Strong programming skills in Kotlin or Java, with experience in high-performance backend systems, Protocol Buffers, and MySQL.
• Strategic Leadership: Demonstrated ability to contribute to team strategy without supervision and influence the broader organizational roadmap.

Technologies We Use and Teach:

• Backend: Kotlin, Java 16, Hibernate, Guice, Jersey
• Search/Data: Elasticsearch, FAISS, Redis, DynamoDB
• Communication: Protocol Buffers, HTTP, JSON
• Infrastructure: AWS, Kubernetes, Buildkite, Datadog

Salary Range:

Canada: the pay range for this role is $190,500 - $262,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

• AI behavior analysis
• Intent recognition evaluation
• Conversation quality assessment
• Model output auditing
• Light prompt testing and refinement

Responsibilities:

• Execute structured test plans for AI Agent implementations
• Validate that intents, entities, and workflows trigger correctly
• Identify behavioral inconsistencies, misclassifications, or hallucinations
• Review and validate AI-generated suggestions, summaries, and classifications
• Provide actionable feedback to improve intent models and redaction/PII handling
• Run bias, redaction, and transcription accuracy checks
• Spot patterns or emerging issues across test sets
• Contribute ideas for improving internal QA processes and tools

Qualifications We Value:

• AI/ML, NLP, or chatbots
• Product quality and user experience
• Linguistics, conversation analysis, or human–AI interaction
• Exploring a career in AI evaluation, AI ops, or product QA

Perks & Benefits:

• $30-$50 per hour subject to taxes
• Lunch can be expensed (up to $25) while working in the office.
• PT0: 4 days

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.com.

Responsibilities:

• Assist with all stages of our AI Delivery projects - designing, building, deploying, and tuning AI solutions for multiple customers.
• Collaborate with internal and external stakeholders to design and build solutions that help customers achieve their business objectives using Cresta's AI product suite.
• Assist in designing solutions for contact centers in sales, retention, collections, and customer service across a range of verticals, from financial services to telecommunications and everything in between.
• Define labeling guidelines to be used to train conversational AI models, and assist with labeling as needed.
• Lead model maintenance efforts to ensure that Cresta's AI models continue to meet our quality standards.
• Design and develop virtual agent solutions using Google's Dialogflow CX.

Qualifications We Value:

Product Manager - Computer Vision & Data Products (Canada, Remote)

Events in recent years have made us all too familiar with the havoc that natural disasters can wreak, and the increasing frequency and intensity with which they are occurring. Despite record levels of losses, conventional methods of identifying and managing risk continue to provide an incomplete solution to these threats.

ZestyAI uses novel data gathering and machine learning approaches to produce higher quality information about the risks to property from catastrophes like severe convective storms and wildfires. While AI alone may not be able to thwart these disasters, it can help communities around the world become more prepared for them, and ultimately that will lead to better outcomes for business and society.

As a Product Manager - Computer Vision and Data Products, you are an analytical thinker and passionate about working with complex data. You are a pacesetter who wants to deliver innovative products; you are organized, self-directed, committed to innovation, and possess outstanding EQ and communication skills. You will be crucial in operating the ZestyAI platform and delivering property characteristics and risk information to our clients. You thrive in a collaborative and creative environment that moves fast and are comfortable learning new skills, leveraging the latest AI tools, and working with unfamiliar technologies.

The Opportunity:

• Own the product and feature development lifecycle from inception to launch in the field of machine learning, large language models, and computer vision
• Build the analytics and model development roadmap of data and risk solutions by researching and analyzing various sources of information
• Discover and translate data into tractable data science questions and engineering specifications to guide strategic decision making
• Work closely with data scientists and software engineers as a key member of the product development team
• Act as the model owner and subject matter expert when interfacing with Regulators and Customers
• Iterate rapidly on everything; all of the above happens in a fast-paced business-driven environment that you must be comfortable with
• Work with our customers to understand complex workflows and pain points and find solutions to the problems

What You Bring to the ZestyAI Team:

• 3-6 years of work experience in analytics, data science, financial modeling, risk modeling, climate modeling or other relevant field

○  Including 1-2 years of Product Management experience, working with data products or model-based features such as actuarial risk model, climate risk model, credit risk model, search model, etc.

• Bachelor's or Master's in a quantitative field such as Engineering, Sciences, Commerce
• Outstanding communication skills, well-versed in building executive-style presentations
• Ability to manage multiple/competing priorities and deliver on time
• Comfortable leveraging AI tools to automate and accelerate everyday work (i.e. Claude Cowork)
• Proficient in SQL, Excel, Python
• Must be legally eligible to work in Canada

Nice to Have:

• Exposure to insurance, real estate, and risk modeling
• Experience working with computer vision models

Why ZestyAI:

• Be a part of a well-funded growth-stage start-up
• Work with a high-performance product team and cutting-edge development team
• Market competitive comp and equity incentives to give you a stake in our future
• Remote-first policy
• Flexible Time Off
• Comprehensive benefits package
• Home office setup stipend
• Annual Learning and Development allowance
• An upbeat and collaborative work culture
• Company-sponsored outings and offsites

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 4+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints.

You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 2+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $165,500 to $227,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About this role

As a Senior Applied AI/ML Scientist on the Search ranking team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site). You will advance real-time search and recommendation systems that power next-generation shopping experiences.

You’ll work at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query.

This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers.

What you'll do

• Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire
• Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents. 
• Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond.
• Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
• Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.

You're a great fit if you have...

• 5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking
• A Master’s or PhD in Computer Science, Statistics, or a related STEM field.
• Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark).
• Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains.
• A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production.
• Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team.

Bonus points for...

• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
• Industry experience developing and productizing LLM-based applications and systems in the search domain.
• Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces.
• Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity.
• Familiarity with Kotlin

Salary Range

California: the pay range for this role is $192,000 to $264,000 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Location

This role requires working from the downtown Toronto office 4 days/week (Mon, Tues, Thurs, Fri). Candidates must be based within a 50-mile commuting distance of the office. 

About the Role

As a Finance Automation Lead at Opendoor, you will join the Finance team reporting to the President of Opendoor with a mandate to 10x our data leverage across Finance. This is a high-impact IC role at the intersection of data architecture, AI engineering, and financial systems.

Opendoor has adopted a "Default to AI" philosophy—if AI can handle it, AI should handle it. We're not theorizing about AI transformation; we're shipping it. You are a builder with a product mindset who will help transform Finance from a service function into a product—one that delivers real-time insights, automated workflows, and self-service capabilities to every team at Opendoor. You understand how LLMs work, you’ve built agents, and you understand how finance data can be leveraged and structured with these models. 

Build AI-Powered Finance Infrastructure

• Design and deploy AI agents that automate data fetching, analysis, reporting, and forecasting workflows

• Architect data pipelines connecting financial planning systems (Adaptive) to Snowflake and downstream applications

• Build semantic layers that enable non-technical finance team members to access data through natural language

Create Finance Tools & Products

• Develop internal tools that transform manual finance processes into automated, scalable products

• Build dashboards and self-service interfaces that eliminate analyst bottlenecks

• Create systems that enable managers to answer their own headcount, budget, and forecast questions without finance intervention 

Own Data Architecture for Finance

• Organize finance data for best-in-class LLM capabilities

• Design data models that support automated analysis, real-time querying, and AI agent interactions

• Establish data quality frameworks and governance for financial systems

Drive Automation at Scale

• Identify high-value automation opportunities across Finance (accruals, reporting, forecasting, variance analysis)

• Implement workflow automation using tools like Gumloop, Claude, and custom-built agents

• Measure and improve automation accuracy, reducing manual intervention over time

What You Will Bring

Technical Foundation

• At least 3+ years of experience building data systems in a finance, analytics, or data engineering role

• Track record of building and deploying AI agents or LLM-powered applications in production environments

• Advanced SQL proficiency with ability to design complex data models and optimize query performance

• Production experience with Python for data engineering, automation, and AI agent development

• Hands-on experience with modern data warehouses (Snowflake, BigQuery, or similar)

AI & Automation Expertise

• Deep understanding of LLM capabilities, limitations, and prompt engineering best practices

• Experience architecting semantic layers or natural language interfaces for data access

• Familiarity with AI orchestration frameworks (LangChain, LlamaIndex, or similar)

• Proven ability to identify high-ROI automation opportunities and implement end-to-end solutions

• Experience with workflow automation tools and API integrations

Data Architecture & Systems Design

• Strong data modeling skills with focus on enabling both human analysts and AI agents

• Experience designing data pipelines that connect planning systems (like Adaptive, Anaplan) to data warehouses

• Understanding of data governance, quality frameworks, and metadata management

• Ability to architect scalable systems that reduce analyst bottlenecks and enable self-service

Product & Business Mindset

• Builder mentality with ability to ship functional products, not just analyses

• Experience translating messy business problems into clean technical solutions

• Strong stakeholder management skills with ability to influence senior finance leadership

• Comfort working in ambiguous, fast-moving environments with evolving requirements

• Systems thinking approach to understanding complex problems and their root causes

Bonus points if you have:

• Experience in fintech, real estate tech, or high-velocity transaction businesses

• Background in financial planning & analysis (FP&A) or corporate finance

• Familiarity with finance-specific tools (Adaptive Insights, NetSuite, etc.)

Compensation

Our compensation plan consists of a base salary, Opendoor equity and a comprehensive package of benefits including paid time off, paid holidays, medical/dental/vision insurance, basic life insurance, and 401(k) to eligible employees.  All compensation parameters are based on experience.

 #LI-DM

#LI-Onsite

Who We Are

At Momentum Financial Services Group, we help people move forward by reimagining how money works for those who need it most. With more than 40 years of experience, we’re the team behind Money Mart—Canada’s largest non-bank branch network—and a leader in financial solutions for underserved communities.

From short-term loans to money transfers and prepaid cards, we power the products, technology, and operations that connect over a million customers a year to the money they need, when they need it.

At MFSG, we come together across teams and departments to create something bigger than ourselves: solutions that remove barriers and give people access to money they might not get anywhere else. Whether you're solving problems, building systems, or shaping strategy, your work fuels real support for real people.

We’ve Got You Covered

Compensation Philosophy: Our strategy is simple—we aim to match the market. We regularly review industry standards to ensure our total rewards package is competitive and fair. This commitment helps us attract and retain talented individuals who share our purpose.

Discretionary Annual Bonus: Enjoy the opportunity for a discretionary bonus based on individual performance and company success.

Comprehensive Benefits: Our benefits include health and dental plans with 100% of the premiums covered. We also offer an Employee Assistance Program to support your mental well-being and provide resources for personal challenges.

Retirement Plans: Plan for your future with our robust retirement savings options, ensuring you’re set for the long haul.

Hybrid Work Environment: Experience the best of both worlds with our hybrid work model, allowing you to balance remote work with in-office. When you're at our corporate head office, enjoy a relaxed and collaborative environment featuring breakout rooms for brainstorming and unwinding, plus a variety of snacks to keep you energized throughout the day.

Perks and Rewards: Enjoy reimbursement for tuition assistance and professional development, discounts through Perkopolis and participate in our rewards and recognition programs to celebrate your contributions.

The Job: Data Scientist

We’re seeking a Data Scientist to develop advanced analytical and machine learning solutions that support credit risk, fraud detection, marketing optimization, and customer segmentation. This role will leverage large-scale data to generate insights, improve decision-making, and drive measurable business impact across the organization.

What You’ll Do

Advanced Analytics & Modeling:

• Design, develop, validate, and deploy predictive and prescriptive models across financial products

• Apply machine learning, statistical, and optimization techniques to solve business challenges such as credit risk, fraud detection, pricing, and customer acquisition

• Ensure models are scalable, compliant, and deliver measurable impact

Data Exploration & Feature Engineering:

• Analyze large and complex datasets to identify patterns and extract meaningful features

• Improve model performance through data-driven insights

Collaboration & Communication:

• Partner with data engineers, product teams, risk teams, and business stakeholders

• Translate business needs into data science solutions and communicate insights effectively

Model Governance & Compliance:

• Ensure models align with regulatory requirements and internal governance standards

• Support audit and validation processes

Continuous Improvement & Innovation:

• Monitor model performance and implement enhancements or retraining

• Explore new tools, techniques, and approaches to improve outcomes

Cross-Functional Initiatives:

• Lead and support projects such as portfolio optimization and customer behavior analysis

• Collaborate across business lines including marketing, operations, and card services

What You’ll Bring to the Table

• 2+ years of experience in financial services, credit risk, fraud analytics, or marketing analytics

• 2+ years of experience applying data science to solve business problems

• Strong experience with SQL, Python, R, or similar analytical tools

• Ability to perform descriptive, diagnostic, predictive, and prescriptive analytics

• Strong problem-solving skills with the ability to translate data into actionable insights

Education + Experience

• Bachelor’s degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, Economics, Finance, or Engineering

• Master’s or PhD in a related field is an asset

Skills & Competencies

• Proficiency in programming languages such as Python (preferred), R, or SAS

• Strong SQL skills for data extraction and analysis

• Experience with machine learning libraries and statistical modeling

• Familiarity with NLP and modern AI techniques (e.g., LLMs) is an asset

• Strong analytical thinking and ability to work with large datasets

Closing

Ready to turn data into impactful insights and drive smarter decisions? Join us and help shape the future of data science at MFSG.

Committed to Equal Opportunity:

MFSG is committed to accommodating applicants up to the point of undue hardship during the recruitment, assessment and selection process. If you are selected for an interview, please notify MFSG if you require accommodation in respect of the materials or procedures used at any time during this process. If you require accommodation, MFSG will work with you to determine how to meet your needs.

Please note: The salary range, inclusive of bonus, for this position is between C$ 95,000 to C$ 105,000.

#SJ

Role Overview

We are looking for a senior to principal product manager to help us build our data platform and own the strategy, roadmap, and execution of Beacon's internal data infrastructure. This is a high-impact, cross-functional role sitting at the intersection of our platform engineering team and our integrations function, which onboards newly acquired companies within 90 days of close.

You will be responsible for partnering with our internal platform engineering team to unify the technology stacks of our portfolio companies into a coherent data platform, building agentic workflows that allow internal teams to query and act on data across the portfolio, and developing products that accelerate our BD and M&A function—from data room preparation to tracking acquisition velocity. This is a senior-level role in scope and ownership.

This is a rare opportunity to build a data platform from the ground up at a firm that moves fast, acquires companies regularly, and genuinely values the work of platform and product teams. You will have high visibility with senior leadership, direct ownership of a critical internal product, and the opportunity to shape how an entire portfolio of software businesses runs on data.

You won't be maintaining someone else's roadmap—you'll be writing it.

What You'll Own

Data Platform Strategy & Architecture

• Define and drive the roadmap for integrating the technology stacks of all Beacon portfolio companies into a unified data platform
• Prioritize which data sources, connectors, and integrations to build, establishing a clear framework for sequencing decisions
• Coordinate with platform engineering to ensure data infrastructure, internal tooling, and portfolio-facing products converge into a coherent, maintainable architecture
• Own the product experience for integration tooling—including templatized onboarding checklists, access tracking, and migration dashboards used by the integrations team
• Identify where we need to provide unified dashboards for business intelligence for leadership to help with GM and portfolio reporting analytics

Agentic Workflows & AI-Powered Products

• Design and ship agentic workflows that allow internal stakeholders to query, analyze, and act on data across the portfolio in natural language
• Evaluate and productize experiments emerging from the GTM engineering team, managing the pipeline from prototype to shipped feature
• Champion AI-native product patterns, leveraging tools like Claude and custom MCP (Model Context Protocol) servers to extend platform capabilities

BD & M&A Enablement

• Build and maintain products that ensure clean, up-to-date data is available in the data room for BD and M&A teams at all times
• Develop tooling to track and improve BD and M&A velocity—surfacing pipeline metrics, diligence timelines, and acquisition progress across deals
• Partner closely with the M&A and Business Development teams to understand their data needs and translate them into platform requirements

Cross-Functional Leadership

• Serve as the connective tissue between platform engineering, the integrations team, and business-side stakeholders (BD, M&A, portfolio GMs)
• Run structured product discovery, write clear PRDs, and drive sprint-level execution with the engineering team
• Define success metrics for the data platform and establish a regular cadence for reviewing progress against them

What We're Looking For

Experience

• 5–10 years of product management experience, with a meaningful portion spent on data platforms, internal tools, or developer-facing products
• Demonstrated experience owning complex, cross-functional product roadmaps with multiple stakeholder groups
• Prior experience in a PE-backed, high-growth, or multi-product environment is a strong plus
• Background as a software engineer, startup founder, or in a technical IC role is a significant plus

Nice-to-Have Skills:

• Strong technical fluency—you can read code, write lightweight scripts, and hold your own in architecture discussions with engineers
• Hands-on familiarity with AI tools, including Claude or similar LLMs, for both personal productivity and product development
• Experience building or working with MCP (Model Context Protocol) servers, or demonstrated comfort building agentic AI workflows
• Familiarity with data integration patterns, APIs, webhooks, ETL pipelines, and CRM/support platform data models (HubSpot, Zendesk, or similar)
• Comfort with SQL and basic data analysis to independently explore datasets and validate product hypotheses

Ways of Working

• Highly autonomous—you take ownership end-to-end, raise blockers early, and keep projects moving without hand-holding
• Structured communicator—you write clear PRDs, crisp project updates, and can translate technical concepts for non-technical audiences
• Builder mindset—you're energized by 0-to-1 problems and are comfortable operating in environments where processes are still being defined
• Curious and adaptable—Beacon operates across many verticals, and you enjoy getting up to speed quickly on new domains

Boosted.ai is building AI purpose-built for finance to help teams do more. Our mission is to optimize investing and boost productivity. We’re already trusted by leading enterprises and developers with over $5T under management with Boosted.ai.

From the fastest growing hedge funds to global financial institutions, our tool lets our users stay ahead of the competition with AI that works for them. We believe that modern investment professionals will win the future of finance by using the best tools; a unique competitive edge powered by data, experimentation, and automation.

Boosted.ai is the platform they use to cut through data overload, outpace competitors, and reclaim their time. We’re looking for sharp, low-ego people to help teams find their edge.

Why is Boosted.ai the best place to work?

• Our product is used every day by investors at the world’s largest financial institutions and most popular investment platforms
• We’re scaling quickly. We have ramped roughly 5× over the past year and growth is accelerating
• We’ve built a culture people actively want to be part of. Many of our strongest applicants come from firms that already use Boosted.ai
• We’re well-capitalized and long-term focused, backed by investors who have helped define modern fintech and enterprise software, including Spark Capital, Ten Coves Capital, Portage Ventures, and RBC.

Position Description

Boosted.ai is seeking a highly motivated, results-oriented Client Solutions Developer to join our rapidly growing team. In this role, you will partner closely with our clients—especially large enterprise accounts—and internal stakeholders to turn client needs into concrete technical solutions. You will build client-facing demos and proofs-of-concept, develop internal tooling for agent evaluation and deployment, and create integrations that connect Boosted.ai to client data sources and workflows.

You will initially focus on mastering our platform, shipping high-quality demos and internal tools, and supporting implementations with well-scoped, maintainable code. You will collaborate with Client Solutions, Engineering, and Product to ensure the successful implementation of our platform (including API-level integrations and data pipelines) and help clients leverage advanced AI technologies to achieve their investment goals. You will also work cross-functionally to reduce delivery overhead, improve reliability, and standardize patterns that make future client work faster and more repeatable. As you grow in the role, you will be expected to take on more strategic responsibilities, such as defining core tooling for agent evaluation, shaping integration patterns, and leading the technical work for major enterprise client engagements.

This is an excellent opportunity for an ambitious developer eager to build a career at the intersection of software engineering, client delivery, and cutting-edge AI technology. We are looking for a candidate who is not only ready to ship production-quality code, but also excited to work directly with client-facing teams, understand real-world constraints, and help design solutions that unlock new AI use cases for the financial industry. If you are a highly motivated, entrepreneurial self-starter with a natural curiosity, we would love to chat!

What You'll Do

• Build client-facing demos and proofs-of-concept that showcase platform capabilities tailored to specific enterprise use cases.
• Develop internal tools for Client Solutions, including evaluation harnesses, prompt management interfaces, and deployment automation.
• Create integration adapters and connectors for client data sources, authentication systems, and workflow tools.
• Automate repetitive delivery workflows to reduce manual overhead and help the team scale.
• Partner with Client Solutions to scope technical requirements and translate client needs into implementable solutions.
• Collaborate with core Engineering on shared infrastructure while maintaining independence for client-specific work.

What We're Looking For

• 3–5 years of professional software development experience with strong fundamentals in at least one backend language (Python preferred) and modern JavaScript/TypeScript.
• Experience building APIs, integrations, and data pipelines, and comfort working with REST, GraphQL, and enterprise authentication patterns.
• Comfort working with LLMs in production contexts, including using LLM APIs and understanding tradeoffs like latency, reliability, and cost.
• Strong foundations in software infrastructure, including debugging production issues, improving reliability, and working with cloud and deployment tooling.
• Familiarity with AI/ML concepts, ideally with hands-on experience using LLM APIs, prompt engineering, or agent frameworks.
• Strong product intuition, with a focus on user problems rather than just technical implementations.
• Excellent communication skills, including working directly with clients and translating between technical and business contexts.
• Ability to work cross-functionally across Client Services, Product, and Engineering, and coordinate effectively in ambiguous environments.
• Ability to move fast and iterate quickly while maintaining high quality and maintainability.
• Comfort with ambiguity and evolving client requirements and priorities.
• Self-direction and the ability to identify valuable work without constant guidance.

Nice to Have

• Experience in fintech, financial services, or enterprise SaaS.
• Background in consulting, professional services, or other client-facing technical roles.
• Familiarity with agent architectures, evaluation frameworks, or prompt engineering best practices.
• Experience with data visualization, dashboarding, or analytics tools.

Expected Achievements

• First 30 Days
  • Complete platform onboarding and gain working knowledge of the agent architecture and integration patterns.
  • Ship your first internal tool or automation that improves team productivity.
  • Build relationships with Client Solutions and understand their most pressing tooling needs.
  • Review existing client demos and identify opportunities for improvement or standardization.
• First 60 Days
  • Deliver a client-facing demo or proof-of-concept for an active sales opportunity.
  • Establish a development workflow that enables rapid iteration on client requests.
  • Contribute to at least one enterprise integration project and gain context on client technical environments.
  • Document patterns and create reusable components that speed up future development.
• First 90 Days
  • Complete a significant automation project that measurably reduces manual delivery overhead.
  • Build credibility with enterprise clients as a reliable technical resource.
  • Establish cross-functional relationships with Engineering and Product that enable effective collaboration.

Compensation

At Boosted.ai, we believe in fair and transparent compensation practices. The base salary range for this full-time position is CAD $110,000 – $130,000, which represents the minimum and maximum target salary for new hires in this role. Actual salary will be determined based on factors such as experience, skills, and location. In addition to base salary, this role is eligible for equity participation by way of stock options, subject to the terms of the applicable plans and policies.

Our Values

We are guided by a set of values that are at the core of our actions and define our culture. These principles are the foundation of our work, and we are committed to upholding them in everything we do.

• Collaborative – We value our team and know that success can only come from working together
• Client Centric – Our focus is always on our clients and consistently delivering them value
• Action Oriented – We remove barriers and we seek to improve in measurable ways
• Accountable – We are accountable for ourselves, and we hold each other accountable
• Respectful – We are proud of our work, we are respectful of each other’s opinions, and we keep a positive attitude

What we offer

We want our benefits to reflect our values and offer the following to full-time employees:

• Flexible (Unlimited) Paid Time Off
• Medical, Dental, and Vision benefits for you and your family
• Life Insurance and Disability Benefits
• Paid Parental Leave
• Free access to use Boosted.ai Alfa™ to make money
• We love the energy of in-person collaboration while also offering the flexibility to work from home when needed

These benefits are further detailed in Boosted.ai’s policies and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Boosted.ai’s equity plans subject to the terms of the applicable plans and policies.

Be you, with us

We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, colour, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

This posting is for an existing vacancy. We do not use artificial intelligence to screen, assess, or select applicants. All candidates who are interviewed will be notified of our hiring decision within 45 days of their last interview.

About You

You are passionate about quality engineering and excited about the intersection of AI and software testing. You thrive in collaborative environments and want to work with cutting-edge technologies while ensuring exceptional user experiences. You appreciate ownership, recognition, and working directly with experienced founders who have launched products from conception to market success.

What You'll Do

Core Responsibilities

Comprehensive Testing & Quality Assurance

• Design and execute testing strategies across mobile, web, voice, wearable, and OTT applications to ensure robust application quality
• Execute functional, exploratory, regression,automated, and AI-assisted testing and troubleshooting defects
• Deploy and maintain AI-enhanced testing frameworks to streamline testing processes and improve accuracy
• Conduct performance, security, and accessibility testing to ensure compliance with modern standards

AI-Enhanced Testing

• Leverage generative AI platforms to create intelligent test cases, automate maintenance tasks, and conduct risk-based testing analysis
• Assist in implementing machine learning-based testing solutions for predictive defect detection and test optimization
• Analyze large-scale testing data using AI-driven analytics for insights and improvements
• Support the development and monitoring of automated test scripts with self-healing capabilities

Collaborative Quality Engineering

• Define testing strategies that ensure software quality throughout the entire SDLC
• Partner with cross-functional teams (developers, designers, product managers) in Agile environments
• Participate in shift-left testing practices, engaging from requirements gathering through production deployment
• Mentor junior team members in modern testing methodologies and AI tool adoption

Strategic Testing Innovation

• Consult with clients to understand testing requirements and define quality metrics
• Research and implement emerging testing technologies and methodologies
• Drive continuous improvement initiatives and champion quality engineering best practices
• Contribute to test automation strategy and CI/CD pipeline optimization

Required Qualifications

Technical Excellence

• Experience: 3-5 years in software testing and quality assurance with focus on mobile applications (iOS, Android)
• Education: Bachelor's or Master's degree in Computer Science, Engineering, or related field
• Programming: Proficiency in JavaScript, TypeScript, Python, Java, or similar languages with OOP concepts
• Automation Expertise: Hands-on experience with Playwright, Cypress, Appium, Selenium, and modern test frameworks
• AI/ML Fundamentals: Understanding of machine learning concepts, data analysis, and AI-powered testing tools
• API Testing: Experience with REST APIs using tools like Postman, Charles Proxy
• Version Control: Proficiency with Git and collaborative development workflows

Modern Testing Competencies

• AI-Powered Testing: Experience with generative AI testing tools and natural language test creation
• Data Analytics Fundamentals: Ability to assess data quality, interpret testing metrics, and extract actionable insights from test results
• CI/CD Pipeline Integration: Experience integrating automated tests into continuous integration pipelines
• Cross-Platform Testing: Proficiency testing applications across multiple browsers, operating systems, and device types to ensure consistent user experience
• Accessibility Testing: Understanding of WCAG guidelines and accessibility testing
• Performance Testing: Knowledge of JMeter, load testing, and performance optimization techniques
• Security Testing: Familiarity with security testing practices, vulnerability assessment, and compliance standards

Essential Skills

• Analytical Thinking: Strong problem-solving, debugging, and root-cause analysis capabilities
• Communication: Excellent written and verbal communication with technical and non-technical stakeholders
• Agile Methodology: Deep understanding of Agile/Scrum practices and iterative development
• Quality Advocacy: Passionate about pushing quality boundaries and motivating teams toward excellence
• Adaptability: Ability to quickly learn new technologies and adapt to changing requirements

Bonus Qualifications

Advanced Technical Experience

• Experience building automated test frameworks from scratch
• Native mobile testing with XCUITest, Espresso, or similar frameworks
• Experience with AI testing platforms (Functionize, Mabl, testRigor, KaneAI)
• Knowledge of containerization (Docker, Kubernetes) for test environment management

Specialized Knowledge

• Experience testing AI/ML models and algorithms
• IoT and connected device testing experience
• Blockchain or cryptocurrency application testing
• Background in data science or machine learning engineering

Key Performance Indicators

Quality Metrics

• Defect detection rate and severity analysis
• Test coverage and automation ratio improvements
• Customer-reported defect reduction percentage

Innovation & Efficiency

• AI tool adoption and ROI measurement
• Test execution time reduction through automation
• Process improvement initiatives implemented
• Team collaboration effectiveness scores

Professional Development

• Continuous learning and certification achievements
• Knowledge sharing and mentoring contributions
• Cross-functional collaboration success metrics