# Senior Applied Scientist - Behavior AI

**Company:** [Datadog](https://hotfix.jobs/companies/datadog)
**Location:** Paris, France
**Role:** AI Research
**Experience:** 5+ years
**Skills:** Machine Learning, Applied Mathematics, Gpu Optimization, Model Training, Model Fine-Tuning, Data Pipelines, Stream Processing, Model Interpretability, Sequence Architectures, Production Systems, Python, Anomaly Detection
**Posted:** 2026-08-12

> Build and optimize custom AI models for real-time anomaly detection across high-throughput security data. The role combines applied mathematics, model training, GPU and systems optimization, production deployment, interpretability, and ongoing model operations.

## Job Description

## Responsibilities
- Design and build custom mid-size models for high-throughput stream processing, and train them at scale.
- Optimize models end to end across mathematics and systems, including mathematical reformulations that better fit hardware and software constraints.
- Build training-data pipelines from raw streams to training-ready datasets.
- Work with engineering to integrate models into production, focusing on GPU utilization, latency, and cost per record on live traffic.
- Plan model and system improvement roadmaps based on product understanding and user needs.
- Build an agentic layer to analyze, validate, and act on model outputs.
- Build lightweight interpretability tools to explain model behavior.
- Maintain and monitor owned models, services, and infrastructure, and participate in the on-call rotation.

## Requirements
- BS, MS, PhD, or equivalent experience in Computer Science, Engineering, Machine Learning, Applied Mathematics, or a related scientific field.
- Hands-on experience training and fine-tuning models at scale and deploying them in production systems with throughput and cost constraints.
- Working knowledge of GPUs and experience optimizing models for real hardware constraints.
- Strong applied mathematics fundamentals.
- Passion for applied mathematics, software design, and implementation.
- Ability to build data pipelines and production code in addition to models.
- Care for code simplicity and performance.
- Ability to explain complex ideas and trade-offs clearly to engineering and product partners.

## Nice-to-haves
- Experience with efficient sequence architectures.
- Experience with model interpretability.
- Experience with large-scale streaming systems.

## Benefits
- New-hire stock equity (RSUs) and employee stock purchase plan (ESPP).
- Continuous professional development, product training, and career pathing.
- Opportunities to attend and present at conferences and meetups and publish work.
- Intra-departmental mentor and buddy program.
- Inclusive company culture and employee resource groups through Community Guilds.
- Competitive global benefits.

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