Senior Machine Learning Engineer

DraftKings Inc.

Senior Machine Learning Engineer at DraftKings developing scalable machine learning systems. Collaborating with cross-functional teams to design and deploy innovative data-driven solutions.

Posted 7/14/2026full-timeNew York City • Massachusetts, New York • 🇺🇸 United StatesSenior💰 $134,400 - $168,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and deploying scalable machine learning systems, with a strong foundation in machine learning, statistics, and the full machine learning lifecycle. Proficient in optimizing model performance and implementing monitoring systems to ensure reliability and accuracy in production environments.

Highest-signal resume keywords

Machine Learning Lifecycle ManagementPython ProgrammingDatabricks ExperienceKubernetes ProficiencyStatistical Validation Frameworks

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningArtificial IntelligenceData PreparationFeature EngineeringModel OptimizationStatistical AnalysisModel MonitoringPerformance EvaluationScalable Systems DesignProduction Readiness

Soft Skills

Strong CommunicationLeadershipCollaborationMentoringProactive Problem Solving

Tools & Technologies

TerraformKubernetesDatabricksMonitoring SystemsStatistical Frameworks

Industry Keywords

Ethical AI DevelopmentData Drift DetectionModel DecayPerformance DegradationCross-Functional Collaboration

Tech Stack

Tools & technologies

KubernetesPythonTerraform

About the role

Key responsibilities & impact

Design and refine scalable pipelines for training, evaluating, and deploying machine learning models across diverse use cases.
Build rigorous testing and statistical validation frameworks to measure model performance and ensure reliability in production.
Optimize models for production readiness, improving computational efficiency, latency, and resource utilization.
Implement real-time monitoring systems to detect data drift, model decay, and performance degradation, proactively maintaining model accuracy.
Partner with cross-functional teammates to design, build, and deploy end-to-end machine learning applications that scale with business growth.
Champion machine learning best practices, including responsible and ethical AI development, documentation, and reproducibility.
Identify and lead technical initiatives that elevate platform capabilities and advance the team’s machine learning standards.

Requirements

What you’ll need

At least 3 years of software engineering experience designing, building, and operating machine learning and artificial intelligence systems in production environments.
A strong foundation in machine learning and statistics, with proven experience applying them to solve complex, real-world problems.
Hands-on experience managing the full machine learning lifecycle, from data preparation and feature engineering to deployment and monitoring.
Expertise in Python, along with experience in additional languages or tools that support scalable machine learning systems.
Experience working with modern platform and infrastructure technologies such as Databricks, Kubernetes, and Terraform.
Strong communication and leadership skills, with the ability to influence stakeholders and collaborate effectively across teams.
A passion for mentoring teammates, sharing knowledge, and fostering technical growth within the team.
The ability to work autonomously, proactively identifying opportunities and driving technical improvements from idea to execution.

Benefits

Comp & perks

health insurance
equity and bonuses