Talent Coordinator

Posted 23 Days Ago
New York, NY
In-Office
80K-120K Annually
Entry level
Machine Learning • Generative AI
The Role
As a Talent Coordinator, you will enhance the candidate experience by coordinating interviews, maintaining the ATS, and improving hiring processes.
Summary Generated by Built In
About Us:

Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. Companies like Suno, Lovable, and Substack rely on Modal to move from prototype to production without the burden of managing infrastructure.

We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.

Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open-source projects (e.g. Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

The Role:

Modal builds infrastructure that lets engineers run AI workloads without the usual pain. To do this well, we need exceptional people - and a hiring experience that reflects the care and rigor we bring to everything else.

As our first Talent Coordinator, you’ll be a foundational partner on the Talent team. You’ll help shape how hiring actually works day-to-day: owning interview coordination, candidate communication, and the operational backbone that allows recruiters and hiring managers to do their best work.

This role carries real trust and visibility. You’ll work closely with the Head of Talent, recruiters, interviewers, and candidates, and you’ll have meaningful input into how our hiring process evolves as we scale.

What you’ll do:

  • Champion a thoughtful, respectful, and high-quality candidate experience at every stage of the interview process

  • Coordinate and schedule phone, video, and in-person interviews across multiple roles and time zones, often with complex calendars

  • Serve as a primary point of contact and host for candidates, ensuring they feel informed, supported, and well-prepared

  • Maintain accuracy and integrity in our ATS (Ashby), including job setup, interview plans, and candidate tracking from first touch through offer

  • Develop deep fluency in Ashby and act as a trusted resource for recruiters and hiring partners

  • Ensure interviewers are well-prepared with the proper context, materials, and logistics to run effective interviews

  • Spot friction or inefficiencies in the hiring process and proactively suggest improvements

  • Partner with the talent team on recruiting initiatives such as referrals, interview training, and process iteration

  • Bring an equity and fairness lens to hiring operations, supporting consistent, well-calibrated interview experiences

Requirements:
  • You bring strong operational discipline and notice the details others miss

  • You’re resourceful by default - when something’s unclear, you figure it out

  • You’re comfortable taking initiative and making progress even when the path isn’t perfectly defined

  • You’re thoughtful about candidate experience and notice the small things that make interviews feel human

  • You value timely, thoughtful follow-up and understand how much clarity and responsiveness matter to candidates

  • You communicate with clarity and intention, even when things move quickly.

  • You show up as a reliable teammate who helps others succeed

  • You’re curious, reflective, and always looking for ways to improve how things run

Top Skills

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The Company
HQ: New York City, New York
50 Employees

What We Do

Deploy generative AI models, large-scale batch jobs, job queues, and more on Modal's platform. We help data science and machine learning teams accelerate development, reduce costs, and effortlessly scale workloads across thousands of CPUs and GPUs.

Our pay-per-use model ensures you're billed only for actual compute time, down to the CPU cycle. No more wasted resources or idle costs—just efficient, scalable computing power when you need it.

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