Databricks Green Card Visa Sponsorship Jobs USA
Databricks is one of the more active Green Card sponsors in the enterprise data and AI software space, consistently filing permanent residency petitions for engineering, product, and research roles. For skilled professionals targeting long-term U.S. residency through a high-growth tech employer, Databricks represents a strong option.
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Get Access To All JobsINTRODUCTION
At Databricks, we are passionate about enabling data 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.
Training and customizing state-of-the-art AI models is one of the most demanding workloads in computing, and it sits at the heart of Databricks' Mosaic AI mission. AI Runtime (AIR) is our managed platform for large-scale GPU training and fine-tuning. It gives customers on-demand access to fleets of the latest accelerators and a serverless experience that hides the complexity of provisioning, scheduling, and orchestrating multi-node jobs, with the resilience to keep training running for days or weeks across thousands of GPUs. AIR powers the full spectrum of custom training, from fine-tuning open models to pre-training frontier-scale foundation models, for some of the most sophisticated AI teams in the world.
As a Senior Software Engineer for AI Runtime, you will play a critical role in building and scaling the systems that make large-scale training fast, reliable, and effortless. You will drive the architecture and evolution of the managed GPU training stack, spanning scheduling and capacity, distributed training performance, fault tolerance, and the developer experience of launching and operating jobs at scale. Beyond hands-on contributions to core systems, you will help shape the technical direction for AIR, mentor other engineers, partner across product, research, and platform teams, and contribute to the initiatives that expand the technical and business impact of custom training at Databricks.
ROLE AND RESPONSIBILITIES
- Drive the architecture and evolution of AIR's managed GPU training platform, delivering scalable, high-throughput, and resilient training across fleets that span thousands of accelerators.
- Solve the hardest problems in large-scale training, including multi-node orchestration, distributed parallelism strategies, GPU scheduling and dynamic routing, high-throughput data loading, and checkpoint and restore for very long-running jobs.
- Push GPU efficiency and training performance, raising utilization (such as model FLOPs utilization and end-to-end throughput) and lowering cost per training run across diverse model architectures and hardware generations.
- Build the resilience and observability foundations that keep multi-node jobs healthy, detecting and recovering from hardware and software failures with minimal disruption to customers.
- Partner with product, research, and platform teams to shape the APIs, CLI, and developer experience that make it easy to launch, monitor, and debug production training jobs.
- Lead end-to-end engineering efforts, from design through production rollout, holding a high bar for performance, correctness, and reliability.
- Make direct, high-impact contributions to the core systems behind AIR, and help bring up support for the latest accelerators and new regions as the fleet grows.
- Champion engineering excellence, mentor other engineers through design reviews and technical discussions, and contribute to Databricks' technical direction in AI training infrastructure.
BASIC QUALIFICATIONS
- 5+ years of experience building and operating large-scale distributed systems, with experience in GPU training infrastructure, high-performance computing, or ML systems.
- Experience with distributed training frameworks (such as PyTorch, FSDP, DeepSpeed, or Megatron) and the parallelism strategies (data, tensor, pipeline, and sequence parallelism) used to train large models.
- Strong understanding of training resilience patterns, including checkpointing, failure detection, and automatic recovery for long-running, multi-node jobs.
- Solid grasp of GPU performance fundamentals, including accelerator architecture, high-speed interconnects (such as NVLink and InfiniBand or RoCE), collective communication, and the bottlenecks that govern training throughput and utilization.
- Experience building and operating managed, multi-tenant platform products in the cloud, with clear SLAs and SLOs for availability, performance, and reliability.
- Strong foundation in algorithms, data structures, and system design as applied to performance-sensitive, large-scale distributed systems.
- Proven ability to deliver technically complex, high-impact initiatives that create clear customer or business value.
- Strong communication skills and the ability to collaborate across product, research, and infrastructure teams in a fast-moving environment.
- Customer-focused mindset with the ability to align implementation details with product goals, and a passion for mentoring engineers and fostering technical excellence.
- BS in Computer Science or a related field (MS or PhD preferred).
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.
Local Pay Range
$160,000—$225,000 USD
ABOUT DATABRICKS
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
BENEFITS
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
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.
INTRODUCTION
At Databricks, we are passionate about enabling data 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.
Training and customizing state-of-the-art AI models is one of the most demanding workloads in computing, and it sits at the heart of Databricks' Mosaic AI mission. AI Runtime (AIR) is our managed platform for large-scale GPU training and fine-tuning. It gives customers on-demand access to fleets of the latest accelerators and a serverless experience that hides the complexity of provisioning, scheduling, and orchestrating multi-node jobs, with the resilience to keep training running for days or weeks across thousands of GPUs. AIR powers the full spectrum of custom training, from fine-tuning open models to pre-training frontier-scale foundation models, for some of the most sophisticated AI teams in the world.
As a Senior Software Engineer for AI Runtime, you will play a critical role in building and scaling the systems that make large-scale training fast, reliable, and effortless. You will drive the architecture and evolution of the managed GPU training stack, spanning scheduling and capacity, distributed training performance, fault tolerance, and the developer experience of launching and operating jobs at scale. Beyond hands-on contributions to core systems, you will help shape the technical direction for AIR, mentor other engineers, partner across product, research, and platform teams, and contribute to the initiatives that expand the technical and business impact of custom training at Databricks.
ROLE AND RESPONSIBILITIES
- Drive the architecture and evolution of AIR's managed GPU training platform, delivering scalable, high-throughput, and resilient training across fleets that span thousands of accelerators.
- Solve the hardest problems in large-scale training, including multi-node orchestration, distributed parallelism strategies, GPU scheduling and dynamic routing, high-throughput data loading, and checkpoint and restore for very long-running jobs.
- Push GPU efficiency and training performance, raising utilization (such as model FLOPs utilization and end-to-end throughput) and lowering cost per training run across diverse model architectures and hardware generations.
- Build the resilience and observability foundations that keep multi-node jobs healthy, detecting and recovering from hardware and software failures with minimal disruption to customers.
- Partner with product, research, and platform teams to shape the APIs, CLI, and developer experience that make it easy to launch, monitor, and debug production training jobs.
- Lead end-to-end engineering efforts, from design through production rollout, holding a high bar for performance, correctness, and reliability.
- Make direct, high-impact contributions to the core systems behind AIR, and help bring up support for the latest accelerators and new regions as the fleet grows.
- Champion engineering excellence, mentor other engineers through design reviews and technical discussions, and contribute to Databricks' technical direction in AI training infrastructure.
BASIC QUALIFICATIONS
- 5+ years of experience building and operating large-scale distributed systems, with experience in GPU training infrastructure, high-performance computing, or ML systems.
- Experience with distributed training frameworks (such as PyTorch, FSDP, DeepSpeed, or Megatron) and the parallelism strategies (data, tensor, pipeline, and sequence parallelism) used to train large models.
- Strong understanding of training resilience patterns, including checkpointing, failure detection, and automatic recovery for long-running, multi-node jobs.
- Solid grasp of GPU performance fundamentals, including accelerator architecture, high-speed interconnects (such as NVLink and InfiniBand or RoCE), collective communication, and the bottlenecks that govern training throughput and utilization.
- Experience building and operating managed, multi-tenant platform products in the cloud, with clear SLAs and SLOs for availability, performance, and reliability.
- Strong foundation in algorithms, data structures, and system design as applied to performance-sensitive, large-scale distributed systems.
- Proven ability to deliver technically complex, high-impact initiatives that create clear customer or business value.
- Strong communication skills and the ability to collaborate across product, research, and infrastructure teams in a fast-moving environment.
- Customer-focused mindset with the ability to align implementation details with product goals, and a passion for mentoring engineers and fostering technical excellence.
- BS in Computer Science or a related field (MS or PhD preferred).
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.
Local Pay Range
$160,000—$225,000 USD
ABOUT DATABRICKS
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
BENEFITS
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
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.
Job Roles at Databricks
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Get Access To All JobsTips for Finding Databricks Green Card Jobs
Target engineering and data roles
Databricks overwhelmingly sponsors Green Cards for software engineers, data scientists, and machine learning roles. Focusing your application on these technical functions gives you the best chance of landing a position where Green Card sponsorship is standard practice.
Clarify sponsorship intent early
During interviews, ask directly whether the role includes Green Card sponsorship as part of the compensation package. At Databricks, this is common in technical hiring but confirming early avoids surprises after an offer is extended.
Understand the PERM process timeline
Green Card sponsorship at a company like Databricks typically begins with PERM labor certification, which can take a year or more before an I-140 is even filed. Starting with realistic timeline expectations helps you plan your immigration status accordingly.
Use Migrate Mate to find verified roles
Not every Databricks job listing will clearly state Green Card sponsorship. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history, making it easier to identify Databricks roles where permanent residency support is likely.
Prioritize roles with established sponsorship patterns
Databricks sponsors Green Cards most consistently in its core Technology and Software business lines. Roles in enterprise engineering, platform infrastructure, and applied AI research have the strongest historical alignment with permanent residency filings.
Align your background with Databricks's technical bar
Green Card sponsorship at Databricks is closely tied to specialty occupation criteria. Strengthening your resume with relevant advanced degrees, published work, or demonstrable technical expertise in data and AI significantly improves both hiring and sponsorship outcomes.
Databricks Green Card Visa Sponsorship: Frequently Asked Questions
Does Databricks sponsor Green Card visas?
Yes, Databricks sponsors Green Card visas and is regarded as one of the more active permanent residency sponsors in the enterprise data and AI software industry. Sponsorship is most common for technical roles such as software engineers, machine learning researchers, and data platform specialists, though the process depends on the specific role and business need.
Which departments at Databricks are most likely to receive Green Card sponsorship?
Engineering, applied research, and data science departments account for the majority of Green Card sponsorships at Databricks. Product management and technical program management roles also see sponsorship, though less frequently. Roles in sales, marketing, and general operations are less commonly sponsored for permanent residency.
How do I navigate the Green Card application process at Databricks?
Databricks typically handles Green Card sponsorship through outside immigration counsel. Once you are employed and eligible, the process begins with PERM labor certification filed with the Department of Labor, followed by an I-140 immigrant petition with USCIS. Your employer's immigration team will guide each stage, but being proactive about asking questions helps you stay informed throughout.
How do I estimate how long the Green Card process takes at Databricks?
The full Green Card process commonly takes several years from start to finish. PERM labor certification alone can take one to two years, and I-140 adjudication adds additional time. For applicants born in high-demand countries such as India or China, priority date backlogs can extend the wait considerably beyond the initial filing timeline.
How do I find Databricks Green Card jobs and confirm sponsorship before applying?
Many Databricks job postings do not explicitly state Green Card sponsorship availability, which can make it hard to know what you are applying into. Migrate Mate aggregates verified sponsorship data so you can identify Databricks roles with a documented history of permanent residency support, saving you time and reducing uncertainty during your job search.
What is the prevailing wage for Green Card sponsorship at Databricks?
Employers sponsoring a Green Card through the PERM labor certification process must pay at least the prevailing wage for the role. The Department of Labor determines this rate based on the specific job title, location, and experience level. The prevailing wage is locked in during the PERM filing and applies through the entire Green Card process. You can look up current rates using the DOL's OFLC Wage Search tool.