Strategic Overview
Senior Software Engineer (Backend) - AI/ML Environments at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly. Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks….
The role is listed for Mountain View, California with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
P-78
At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer…
As part of the ML/AI Environments team you will build the system that enables the AI researchers and engineers to set up their desired training and serving environments. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping…
Key Responsibilities & Objectives
- Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly.
- Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks platform. Examples include improving performance of setting up virtual environments for short training and data processing sessions, improving observability to help customers debug when runs fail,…
- Shape how developers and data scientists build and interact with AI on Databricks.
Required Qualifications & Candidate Blueprint
- 5+ years of experience in backend or infrastructure engineering with a focus on building systems
- Strong programming skills in Python, Scala or Java
- Experience with distributed systems, scalable APIs, or cloud-native infrastructure
Salary & Benefits
Published compensation: $166,000 – $220,000 USD
Salary Benchmark
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Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
P-78
At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
As part of the ML/AI Environments team you will build the system that enables the AI researchers and engineers to set up their desired training and serving environments. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI.
The impact you will have
- Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly.
- Collaborate with other AI infrastructure teams to build the features that customers need to get more from the Databricks platform. Examples include improving performance of setting up virtual environments for short training and data processing sessions, improving observability to help customers debug when runs fail, etc.
- Interact with turnkey customers and product managers to envision new features and identify areas for improvement.
- Shape how developers and data scientists build and interact with AI on Databricks.
What we look for
- 5+ years of experience in backend or infrastructure engineering with a focus on building systems
- Strong programming skills in Python, Scala or Java
- Experience with distributed systems, scalable APIs, or cloud-native infrastructure
- Familiarity with service-oriented architecture, deployment pipelines, and system observability
- Strong product and ownership mindset — you care about building the right solution, not just any solution
- Strong understanding of dependency management technologies including virtual environments or containerization technologies.
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.
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Build the infrastructure that enables ML and AI users to configure training and serving environments easily, reliably and reproducibly. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.