Senior Applied Scientist - Behavior AI

The shape of it

In the posting’s own words

We are hiring a Senior Applied Scientist to build these models from start to finish. You will contribute to designing the architecture, training at scale, and the optimization work that takes a model from training to running efficiently on production traffic. This optimization requires a deep understanding of the constraints imposed by both the software and the hardware, together with the applied mathematics to work within them: often it comes down to finding a mathematical reformulation that fits those constraints better, and that judgment can decide whether a model reaches production at all.

What it asks for · 8

• You have a BS/MS/PhD in Computer Science, Engineering, Machine Learning, Applied Mathematics, or a related scientific field, or equivalent experience.
• You have hands-on experience training and fine-tuning models at scale, and deploying them into production systems with real throughput and cost constraints.
• You have a working knowledge of how GPUs work, and a track record of making models run efficiently within real hardware constraints.
• You have strong applied-mathematics fundamentals and reach for them naturally when designing and optimizing models.
• You have a real passion for applied mathematics, software design, and implementation. This role sits at the intersection of the three, and it is a requirement for the position.
• You care about code simplicity and performance, and you can build the data pipelines and the surrounding production code, in addition to the models themselves.
• You can explain complex ideas and trade-offs clearly to engineers and product partners, and you let a solid understanding of the product guide what you build next.
• Bonus: experience with efficient sequence architectures, model interpretability, or large-scale streaming systems.

What the job covers

• Design and build custom mid-size models for high-throughput stream processing, and train them at scale.
• Optimize these models from start to finish, working across both the mathematics and the systems, often by finding mathematical reformulations that fit the hardware and software constraints better.
• Build the training data pipelines the work depends on when they do not already exist, from the raw stream to a training-ready dataset.
• Work with engineering to integrate models into production, with a clear focus on GPU utilization, latency, and cost per record on live traffic.
• Plan the roadmap of model and system improvements, based on a solid understanding of the product and of what matters most to users.
• Build an agentic layer on top of the models to analyze, validate, and act on their outputs.
• Build lightweight interpretability tools that make model behavior easier to explain to the people who rely on it.
• Maintain and monitor the models, services, and infrastructure your team owns, and take part in your team's on-call rotation.

Degree language

• You have a BS/MS/PhD in Computer Science, Engineering, Machine Learning, Applied Mathematics, or a related scientific field, or equivalent experience.

Tools and skills named

Words the posting leans on

• models21×
• build10×
• constraints5×
• product5×
• production5×
• record5×
• fit4×
• real4×
• run4×
• scale4×
• stream4×
• systems4×
• training4×
• applied mathematics3×
• behavior3×
• cost3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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