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DraftKings
DraftKings

Digital sports entertainment and gaming company

Senior Machine Learning Engineer, Personalization

职能机器学习
级别资深
地点Remote - Canada
方式远程
类型全职
发布3周前
立即申请

At Draft Kings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together.

The Crown Is Yours

As a Senior Machine Learning Engineer on the Personalization team, you'll shape how players experience our products by building real-time, one-to-one personalization at scale. You'll design and deploy machine learning systems that deepen engagement, improve retention, and drive long-term player value. Working across Engineering, Product, and Analytics teams, you'll turn data into impactful experiences while advancing how we build, deploy, and optimize ML solutions. This role blends hands-on model development with system design and technical leadership in a fast-moving, high-impact environment.

What You'll Do:

  • Lead end-to-end machine learning initiatives focused on improving player engagement and retention, from initial concept through production deployment.

  • Build scalable, reusable machine learning pipelines with a focus on reliability, maintainability, and performance.

  • Design and manage CI/CD workflows for machine learning using tools like MLflow, Jenkins, and Git Ops to enable automated and efficient model deployment.

  • Monitor model performance in production, implementing retraining strategies, drift detection, and continuous optimization.

  • Partner with cross-functional teams to translate business goals and user insights into high-impact machine learning solutions.

  • Mentor other engineers and help define best practices for machine learning system design, development, and deployment.

What You'll Bring:

  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related technical field.

  • At least 3 years of experience working with machine learning systems in production environments.

  • Strong proficiency in Python and SQL, with experience working on distributed data platforms such as Spark.

  • Proven experience delivering production-grade machine learning models that drive measurable business impact.

  • Hands-on experience with Databricks for managing machine learning workflows, model lifecycle, and collaborative development.

  • Experience designing experiments and analyzing A/B tests to validate and optimize model performance.

  • Strong communication and collaboration skills, with experience mentoring or leading technical initiatives.

Join Our Team

We’re a publicly traded (NASDAQ: DKNG) technology company headquartered in Boston. As a regulated gaming company, you may be required to obtain a gaming license issued by the appropriate state agency as a condition of employment. Don’t worry, we’ll guide you through the process if this is relevant to your role.

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关于DraftKings

DraftKings

DraftKings is a digital sports entertainment and gaming company that operates daily fantasy sports contests and online sportsbook betting. The company offers mobile and web-based platforms for users to participate in fantasy sports and place sports wagers.

1,001-5,000

员工数

Boston

总部位置

$12.5B

企业估值

评价

10条评价

3.0

10条评价

工作生活平衡

3.2

薪酬

3.8

企业文化

2.8

职业发展

2.5

管理层

2.1

45%

推荐率

优点

Good compensation and benefits

Flexible working arrangements

Fun work environment and products

缺点

Poor management and leadership issues

Lack of communication

Limited growth opportunities

薪资范围

55个数据点

Junior/L3

Mid/L4

Senior/L5

Director

Junior/L3 · Data Engineer

4份报告

$126,100

年薪总额

基本工资

$97,000

股票

-

奖金

-

$126,100

$126,100

面试评价

5条评价

难度

3.2

/ 5

时长

14-28周

体验

正面 0%

中性 80%

负面 20%

面试流程

1

Application Review

2

Online Assessment

3

Recruiter Screen

4

Technical Phone Screen

5

Final Interview

6

Offer Decision

常见问题

Coding/Algorithm

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit