Senior Applied AI Scientist - Scalable ML for Observability

Datadog; City of Niagara Falls (NY); Hybrid; USD 220,000 - 275,000; Full time

Benefits offered by this job

RSUs

Conference attendance

Mentor program

Inclusive culture

Job summary

Datadog is seeking an Applied Scientist to design and build machine learning powered features for the Datadog platform. You will work on anomaly detection, error outliers, and deployment analysis with engineering and product partners across New York City and Paris.

You will develop, deploy and monitor models in production, benchmark algorithms, and communicate insights to non-technical stakeholders while emphasizing performance and scalability.

Qualifications

• BS/MS/PhD in Computer Science, Engineering, ML, or related field
• Experience with high-scale systems and datasets, including building models and data pipelines
• Ability to explain complex ideas to non-technical audiences
• Care about code simplicity and performance
• Excited to work on a user-facing product

Responsibilities

• Design ML solutions for diverse use cases and benchmark algorithms
• Leverage ML and statistics to build scalable product features
• Develop, deploy and monitor features in production
• Participate in journal club to discuss latest research papers
• Analyze large volumes of data and tell the story behind it
• Maintain models, services and infrastructure owned by the team
• Join the team on-call rotation

Skills

Machine learning

High-scale systems

Data pipelines

Production deployment

Communication skills

Education

BS/MS/PhD in Computer Science or related field

Job description

Datadog is seeking an Applied Scientist to design and build machine learning powered features for the Datadog platform. You will work on anomaly detection, error outliers, and deployment analysis with engineering and product partners across New York City and Paris.

You will develop, deploy and monitor models in production, benchmark algorithms, and communicate insights to non-technical stakeholders while emphasizing performance and scalability.