Pay
In line with similar jobs
$166K–$210K against $166K–$240K, the middle half of what similar US postings state.
From 1,394 postings in the last year. Stated ranges, not salaries paid.
Senior Applied ML Engineer - ML4Sys
San Francisco, California
Open 3 months, first seen by us 92 days ago- Pay
USD 166,000–210,250/yearAnnual period assumed — pay source
Local Pay Range $166,000—$210,250 USD About Databricks
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- Employer’s visa record
- 620 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.
What you’ll work on
Full postingDesign end-to-end ML solutions for infrastructure efficiency within a lean team
Architect, train and deploy models that improve product performance and cost
Build ML pipelines, data processing layers, model serving and production monitoring
Research and implement novel modeling techniques for computer systems
Define the roadmap for applied ML investments with engineering and product leaders
From the employer’s posting
Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts
Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency
Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems
Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments
Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks
What you’ll bring
All qualificationsCore experience
- Master's degree in computer science or a related computational field
- Strong background building, training and deploying ML models in production
- Practical familiarity with cloud computing, distributed systems and data processing frameworks
- Proficiency in Python, Scala or Java
Qualification wording
Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field
Strong background in building, training, and deploying machine learning models in production
Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks
Proficiency in Python, Scala, or Java
Education & alternatives
Minimum Qualifications - Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc). - ML Experience: Strong background in building, training, and deploying machine learning models in production.
Preferred Skills - Advanced Education: PhD in AI, Data Science, or a related technical discipline. - Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment.
About Databricks
More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.
In the employer’s words · Read in context
Posting record
Report an errorOpen 3 monthsWe first saw this posting 92 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Aug 13, 202692 days ago
- Recorded sightings
- 264
- Last seen by us
- Nov 13, 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 92
Up longer than most. Similar jobs usually come down between day 8 and day 76.
At Databricks, jobs usually come down by about day 63.
From 5,460 similar postings that came down, and 19 of Databricks’s. Coming down is not always a hire.
Databricks is hiring
29 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is picking up
- Its jobs tend to stay up a long time
- 3% 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.
- Java
- Python
- Scala
- Databricks
Where the posting names them
- Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks. - Core Coding: Proficiency in Python, Scala, or Java. Preferred Skills
Summary As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers. Impact You Will Have
Impact You Will Have - Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques. - Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support
- Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support - Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks. - Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency.
Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here. Local Pay Range
$166,000—$210,250 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram. Benefits
Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here. Our Commitment to Diversity and Inclusion
Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance
Your next step
Complete your application on databricks.com. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 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
RDQ127R59
Summary
As a Senior Applied ML Engineer on the Applied AI team at Databricks, you will use machine learning, scheduling, and optimization algorithms to maximize the efficiency and performance of our infrastructure. Your work will span the entire stack—from cluster management down to query compilation. You will solve complex, high-impact engineering problems to deliver highly optimized, cost-effective workloads for our customers.
Impact You Will Have
- Accelerate Serverless Growth: Drive the scaling and efficiency of Databricks serverless compute products through advanced optimization techniques.
- Build Systems: Design end-to-end ML4Sys solutions from the ground up within a lean team of domain experts to support
- Shape Strategy: Define the roadmap for applied ML investments by collaborating with engineering and product leaders across Databricks.
- Drive Deployment: Architect, train, and deploy state-of-the-art models that directly improve product performance and cost efficiency.
- Scale Infrastructure: Build robust ML pipelines, data processing layers, model serving components, and production monitoring systems to help scale
- Innovate: Research and implement novel modeling techniques tailored specifically to computer systems and distributed environments.
Minimum Qualifications
- Education: Background in Computer Science and Master's degree in Machine Learning, Data Science, or a related computational field (AI, Bioinformatics, EE, Physics, etc).
- ML Experience: Strong background in building, training, and deploying machine learning models in production.
- Infrastructure Knowledge: Practical familiarity with cloud computing, distributed systems, and modern data processing frameworks.
- Core Coding: Proficiency in Python, Scala, or Java.
Preferred Skills
- Advanced Education: PhD in AI, Data Science, or a related technical discipline.
- Industry Experience: 4+ years of machine learning engineering experience in high-velocity, high-growth environment.
- Systems Domain: Strong understanding of computer architecture, distributed computing, cloud compute, database internals, or networking.
- Optimization: Experience with operations research, forecasting, markov decision processes, or other optimization algorithms for sequential decision making.
- Scale: Proven track record of optimizing large-scale distributed systems or cloud infrastructure via data-driven approaches.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
Local Pay Range
$166,000—$210,250 USD
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Local Pay Range $166,000—$210,250 USD About Databricks
- Location & working pattern
San Francisco, California
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.