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Software Engineer

Netflix - 1d ago

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Senior Software Engineer

Reddit - 4d ago

Senior Applied Scientist - Behavior AI

Requirements:

  • 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.

Nice to Haves:

  • Bonus: experience with efficient sequence architectures, model interpretability, or large-scale streaming systems.

What You'll Do:

  • 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.

Perks and Benefits:

  • New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
  • Continuous professional development, product training, and career pathing
  • Opportunity to attend and present at conferences and meetups, and to publish your work
  • Intra-departmental mentor and buddy program for in-house networking
  • An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups)
  • Competitive global benefits
AI Summary ✨
Datadog logo

Datadog

Remote - Paris, France (Remote)

Remote
Experience: Senior
Posted: July 6, 2026
Last seen: an hour ago
machinelearning

Why we track Datadog

Datadog has grown fast and has engineering teams across Europe, including Paris where they were originally founded. Observability is a space where the technical challenges are real—high-throughput data, distributed systems, real-time processing.

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