Qureos Mentor

Middesk

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 About Middesk
 
 
 
 Middesk makes it easier for businesses to work together. Since 2018, we&rsquo;ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.
 
 
 Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List.
 
 
 
 The Role:
 
 
 
 As the Workplace Coordinator, you will be the on-the-ground support keeping our San Francisco office running smoothly day to day. This is a contractor role focused on the practical, tactical work that makes the office a great place to be, from keeping supplies stocked and the space well-organized to making sure new hires walk in on day one with everything they need.
 
 
 
 Role Specifications:
 
 
 
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 Start date: May 4, 2026
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 Classification: Part-time employee; hourly
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 Hours: 15-20 hrs/week
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 Flexible schedule, preferable availability including Tuesdays and/or Thursdays
 
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 What You'll Do:
 
 
 
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 Day-to-day office operations. Keep the SF office well-stocked, organized, and functioning. Routinely monitor and replenish supplies, flag maintenance needs, and ensure the space is always ready for the team.
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 Vendor coordination. Serve as the on-site point of contact for building management, maintenance, and delivery vendors. Be present to receive and manage as needed.
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 IT coordination. Serve as the onsite point-of-contact for the third-party IT contractor, supporting basic office IT/AV needs and troubleshooting.
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 New hire desk setup. Own the SF seating chart. Ensure new hire desks are assigned, stocked, and ready before their start date. Greet new hires on their first day and help them get oriented to the space.
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 Space improvement projects. Support office upgrade projects as needed, including coordinating furniture orders and installation, setting up equipment, and helping get new initiatives (like metrics dashboards) off the ground in the space.
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 In-office event support. Provide on-the-ground assistance for occasional in-office events in SF, including setting up the space, coordinating day-of logistics, and helping things run smoothly.
 
 
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 What We're Looking For:
 
 
 
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 A detail-oriented, get-it-done approach; you notice what needs attention and take care of it
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 Comfort working independently and managing your own time on site
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 Friendly, welcoming presence so new hires and employees feel taken care of
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 Reliability and clear communication when flagging issues or coordinating with vendors
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</div>

Workplace Coordinator (Part-time)

<div>
 
 About Middesk
 
 
 
 Middesk makes it easier for businesses to work together. Since 2018, we&rsquo;ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.
 
 
 Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List.
 
 
 
 The Role:
 
 
 
 We&rsquo;re building AI-driven applications that power business onboarding, fraud prevention, and identity verification. With proprietary data assets and deep domain expertise, we&rsquo;re uniquely positioned to create a new generation of ML-powered solutions for trust and risk.
 
 
 We&rsquo;re looking for a
 
 hands-on Machine Learning Engineer with strong Data Science expertise
 
 to take end-to-end ownership of the ML lifecycle: from feature design and model development, to deployment, monitoring, and iteration in production. Unlike larger organizations where responsibilities are split, you&rsquo;ll have the opportunity to
 
 own models from concept to production
 
 while working closely with product managers, engineers, and data platform teammates who support and amplify your work.
 
 
 This is a rare chance to join an
 
 earlier-stage company
 
 where you&rsquo;ll have broad visibility and influence, and where your ML systems will have immediate and measurable impact on customers.
 
 
 What You&rsquo;ll Do:
 
 
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 End-to-end ML ownership: Lead the full lifecycle of ML systems &mdash; feature engineering, model design, training, evaluation, deployment, monitoring, and iteration.
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 Collaborate with a strong team: Work alongside data engineers, platform engineers, and product teammates who ensure you have the infrastructure, data, and context to deliver.
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 Design &amp; deploy production models: Build high-performance ML applications in risk, fraud, trust &amp; safety, and compliance domains.
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 Keep models healthy in production: Proactively monitor, detect drift, and retrain to ensure long-term performance and reliability.
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 Experiment &amp; learn: Drive online experiments, offline evaluation, and counterfactual analyses to prove impact.
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 Shape ML foundations: Contribute to the feature store, model management, training/serving pipelines, and best practices that scale ML across multiple use cases.
 
 
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 What We&rsquo;re Looking For:
 
 
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 4+ years applied ML experience with proven impact in risk, fraud, trust &amp; safety, compliance, fintech, or other high-stakes domains.
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 Track record of owning ML models end-to-end &mdash; from research and design to deployment, monitoring, and retraining in production.
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 Strong software engineering skills (Python, ML frameworks, deployment pipelines) and ability to write reliable, production-grade code.
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 Hands-on experience with ML infrastructure such as feature stores, model management, training/serving pipelines, and monitoring tools.
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 Comfortable as a senior IC: you can set technical direction, establish best practices, and mentor peers while collaborating effectively across teams.
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 Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML systems to life.
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 Deep expertise in classification challenges such as imbalanced labels, sparse signals, cold start, and production version management.
 
 
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 Nice to Haves:
 
 
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 B2B SaaS experience, ideally building ML products for enterprise customers.
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 Familiarity with graph, LLM-based feature generation, or AI agent workflows.
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 Experience scaling ML across multiple products or risk domains.
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Machine Learning Engineer

Join Middesk and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Middesk

About Company

Workplace Coordinator (Part-time)

Machine Learning Engineer