Pay
Lower than most similar jobs
$134K–$168K against $166K–$240K, the middle half of what similar US postings state.
From 1,319 postings in the last year. Stated ranges, not salaries paid.
Senior Machine Learning Engineer
- Pay
USD 134,400–168,000/year · BaseAnnual period assumed. Plus bonus, equity — pay source
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.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDefine architecture and roadmap for the ML platform, including real-time ingestion and ML serving
Design and scale distributed data systems using Kafka, Spark Structured Streaming, and Databricks
Establish engineering standards and guide complex initiatives through design and code reviews
Own reliability and operations of critical platform services, including monitoring and incident response
Drive cloud cost efficiency through resource optimization and cost monitoring
From the employer’s posting
Define the technical architecture and roadmap for our Machine Learning Platform
Design and scale distributed data systems using technologies such as Kafka, Spark Structured Streaming, and Databricks
Establish engineering standards and architectural best practices, driving adoption across teams
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
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 5, 20261 day ago
- Recorded sightings
- 2
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 1
Early. Similar jobs usually come down between day 6 and day 71.
At DraftKings, jobs usually come down by about day 33.
From 4,620 similar postings that came down, and 16 of DraftKings’s. Coming down is not always a hire.
DraftKings is hiring
8 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Takes jobs down at a usual pace
- 13% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- AWS
- Databricks
- Delta Lake
- Iceberg
- Kafka
- Snowflake
- Spark
- Terraform
Where the posting names them
- 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.
- 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.
- 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.
- 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.
- 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
Your next step
Complete your application on draftkings.wd1.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
- You create an account with each employer before you can upload anything. Every Workday employer has its own account, so one sign-up doesn’t carry over.
- “Autofill with Resume” comes right after sign-in, before the My Information and My Experience steps. Check every field it fills in those steps, since that’s what recruiters see.
- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
Has DraftKings posted this job before?
Yes. We’ve followed 3 other Senior Machine Learning Engineer jobs there since July 2026. 2 came down, usually after about 28 days. One is still up.
Large employers often post one title for several teams, so these can be separate openings.
About DraftKings
- People
- About 5,500 in 2025, up 8% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as DKNG.
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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.
- Location & working pattern
Boston, MA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.