Senior Machine Learning Engineer

DK Crown Holdings Inc.; Boston (MA); On-site; USD 134,000 - 168,000; Full time

Job summary

DraftKings in Boston is seeking a Senior Machine Learning Engineer to shape the technical direction of the ML Platform that powers data science, analytics, and ML capabilities across the company. You will lead real-time data pipelines, governance, and scalable ML services, partnering across engineering and data science to raise platform ownership and reliability.

You’ll mentor engineers, drive automation, and set engineering standards while advancing cost-aware, scalable infrastructure and

Qualifications

• 8+ years of experience in software engineering, data engineering, or ML infrastructure.
• Deep expertise in distributed data systems and streaming technologies (Kafka, Spark, Iceberg/Delta Lake).
• Experience with Databricks and lakehouse governance.
• Proficiency with AWS, Terraform, IaC, and cloud networking.
• Ability to define technical architecture and influence multiple teams.
• Experience managing production infrastructure, monitoring, incident response, and reliability.
• Experience with AI-assisted development tools and automation.
• Strong communication and mentorship skills.
• Experience with Snowflake or AI-powered developer tooling is a plus.

Responsibilities

• Define the technical architecture and roadmap for the Machine Learning Platform, including real-time data ingestion, lakehouse governance, and ML serving infrastructure.
• Design and scale distributed data systems using Kafka, Spark Structured Streaming, and Databricks with a focus on reliability, automation, and self-service capabilities.
• Establish engineering standards and architectural best practices, driving adoption across teams to improve platform consistency, scalability, and performance.
• Lead complex engineering initiatives by defining technical specifications, milestones, and guiding implementation through design and code reviews.
• Partner with Data Engineering, BI, Data Science, and Architecture teams to advance data sharing, platform connectivity, and enterprise data infrastructure.
• Own the reliability and operational performance of critical platform services, including monitoring, incident response, and continuous improvement.
• Drive cloud cost efficiency through resource optimization, cost monitoring, and scalable compute management frameworks.
• Champion AI-assisted engineering practices, develop intelligent automation tools, and mentor engineers to strengthen technical expertise and expand platform ownership.

Skills

Distributed data systems

Streaming technologies

Leadership experience

AWS & Terraform

Mentorship

Communication

Tools

Kafka

Spark Structured Streaming

Databricks

Iceberg/Delta Lake

Snowflake

Job description

At DraftKings, 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, you’ll shape the technical direction of the Machine Learning Platform that powers data science, analytics, and machine learning capabilities across DraftKings. You’ll lead the architecture and evolution of critical infrastructure, from real-time data pipelines and data governance to scalable machine learning services. Working across Engineering and Data Science teams, you’ll establish technical standards, drive complex initiatives, and build reliable, efficient systems that support our growing business. Your impact will extend beyond the platform as you mentor engineers, advance automation, and influence how we build and operate machine learning infrastructure at scale.

What you’ll do as a Senior Machine Learning Engineer

• Define the technical architecture and roadmap for our Machine Learning Platform, including real-time data ingestion, lakehouse governance, and machine learning serving infrastructure.
• Design and scale distributed data systems using technologies such as Kafka, Spark Structured Streaming, and Databricks, with a focus on reliability, automation, and self-service capabilities.
• Establish engineering standards and architectural best practices, driving adoption across teams to improve platform consistency, scalability, and performance.
• Lead complex engineering initiatives by defining technical specifications, establishing milestones, and guiding implementation through design and code reviews.
• Partner with Data Engineering, Business Intelligence, Data Science, and Architecture teams to advance data sharing, platform connectivity, and enterprise data infrastructure.
• Own the reliability and operational performance of critical platform services, including monitoring, incident response, and continuous improvement.
• Drive cloud cost efficiency through resource optimization, cost monitoring, and scalable compute management frameworks.
• Champion AI-assisted engineering practices, develop intelligent automation tools, and mentor engineers to strengthen technical expertise and expand platform ownership.

What you’ll bring

• At least 8 years of experience in software engineering, data engineering, or machine learning infrastructure, including experience leading complex technical initiatives.
• Deep expertise in distributed data systems and streaming technologies, including Kafka, Spark or comparable frameworks, schema management, and open table formats such as Apache Iceberg or Delta Lake.
• Strong experience with Databricks or similar lakehouse platforms, including data governance, access management, and scalable data architecture.
• Proficiency with Amazon Web Services (AWS), Terraform, infrastructure as code, and cloud networking and identity management.
• Proven ability to define technical architecture, establish engineering standards, and influence decisions across multiple engineering and data teams.
• Experience managing production infrastructure, including monitoring, on-call support, incident response, and operational reliability.
• Experience with AI-assisted development tools and the ability to apply emerging technologies to improve engineering efficiency and automate workflows.
• Strong communication, collaboration, and mentorship skills, with the ability to translate complex technical concepts into actionable plans and guide engineers at different experience levels.
• Experience with Snowflake, machine learning serving infrastructure, cloud cost optimization, or AI-powered developer tooling is a plus.

#LI-EN1 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.

The US base salary range for this full-time position is 134,400.00 USD - 168,000.00 USD, plus bonus, equity, and benefits as applicable. Our ranges are determined by role, level, and location. The compensation information displayed on each job posting reflects the range for new hire pay rates for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific pay range and how that was determined during the hiring process.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

DraftKings Inc. (Nasdaq: DKNG) is a digital sports entertainment and gaming company. It’s simple, at DraftKings, we believe life’s more fun with skin in the game. For that reason, we’re committed to responsibly creating the world’s favorite games and betting experiences. Headquartered in Boston, with offices around the globe, we believe we can continue to define what it means to be a technology company in sports entertainment. We love what we do, and think you will too.