Machine Learning Visa Sponsorship Jobs in Washington DC
Washington DC's machine learning job market is driven by federal agencies, defense contractors, and policy-focused tech organizations. Employers like Booz Allen Hamilton, Leidos, Palantir, and the broader government contracting sector regularly hire ML engineers and data scientists, many of whom require H-1B visa or O-1 visa sponsorship to work in the district.
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Press Ganey is the leading experience measurement, data analytics, and insights provider for complex industries—a status we earned over decades of deep partnership with clients to help them understand and meet the needs of their key stakeholders. Our earliest roots are in U.S. healthcare – perhaps the most complex of all industries. Today we serve clients around the globe in every industry to help them improve the Human Experiences at the heart of their business. We serve our clients through an unparalleled offering that combines technology, data, and expertise to enable them to pinpoint and prioritize opportunities, accelerate improvement efforts and build lifetime loyalty among their customers and employees.
Like all great companies, our success is a function of our people and our culture. Our employees have world-class talent, a collaborative work ethic, and a passion for the work that have earned us trusted advisor status among the world’s most recognized brands. As a member of the team, you will help us create value for our clients, you will make us better through your contribution to the work and your voice in the process. Ours is a path of learning and continuous improvement; team efforts chart the course for corporate success.
Our Mission:
We empower organizations to deliver the best experiences. With industry expertise and technology, we turn data into insights that drive innovation and action.
Our Values:
To put Human Experience at the heart of organizations so every person can be seen and understood.
- Energize the customer relationship: Our clients are our partners. We make their goals our own, working side by side to turn challenges into solutions.
- Success starts with me: Personal ownership fuels collective success. We each play our part and empower our teammates to do the same.
- Commit to learning: Every win is a springboard. Every hurdle is a lesson. We use each experience as an opportunity to grow.
- Dare to innovate: We challenge the status quo with creativity and innovation as our true north.
- Better together: We check our egos at the door. We work together, so we win together.
Press Ganey is committed to providing reasonable accommodations to qualified individuals with disabilities or disabled veterans in the hiring process. If you need assistance or an accommodation to apply for a position online or for your interviews or assessments, please contact us at acommodations@pressganey.com. Please provide your contact information and the details of your request so we can best assist you.
ROLE AND RESPONSIBILITIES
We are seeking a Staff ML Engineer to lead the design, delivery, and operation of production-grade AI systems. You will build the services and high-throughput pipelines behind our text analytics platform and a growing portfolio of AI products, processing feedback and conversations from every channel our customers use to engage with patients and their customers. The central challenge is sustaining service reliability and measurable AI quality as models, inputs, and volumes change.
As a technical leader, you will guide engineers through design and implementation, contribute directly to the codebase, and lead architectural decisions across teams. Working primarily with Python and cloud-based data and AI platforms, with a growing emphasis on Databricks, you will shape the shared infrastructure supporting both established products and new AI applications.
- Own technical delivery from prototype through deployment and ongoing production support, partnering with AI Scientists and Product to define requirements, plan implementation, and resolve cross-team dependencies.
- Evaluate proposed AI solutions for production suitability, identify technical risks, and choose architectures that meet quality, reliability, and cost requirements without unnecessary complexity.
- Architect and build high-volume AI services and processing pipelines, including fault tolerance, backpressure, retries, idempotency, and recovery from partial failures.
- Lead the evolution of our Python services and Databricks-based platform for distributed processing, model serving, and integration of traditional ML and LLM-based components.
- Establish production engineering standards for automated testing, CI/CD, model and prompt versioning, load testing, controlled rollouts, and rollback.
- Build evaluation and monitoring capabilities to detect AI quality regressions and track service reliability, throughput, latency, and inference cost.
- Partner with Product and Responsible AI teams to define release criteria and implement requirements for model validation, data privacy, security, and governance.
- Optimize processing and inference workloads, balancing model quality, throughput, latency, capacity, and cost.
- Mentor engineers and lead architecture and code reviews, maintaining consistent standards for software quality and maintainability.
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Electrical Engineering, or a related technical discipline, or equivalent practical experience.
- 8+ years of professional software engineering experience, including at least 3 years owning ML or LLM systems in production and their operational support.
- Proven track record of independently leading complex technical initiatives from requirements through production, making architectural decisions and coordinating delivery across stakeholders.
- Advanced proficiency in Python for production services and data processing, with strong SQL skills.
- Experience designing and operating high-throughput distributed systems, with a strong understanding of failure recovery, multi-tenancy, and capacity planning.
- Hands-on experience deploying and operating LLM-based applications, including evaluation, output validation, observability, and cost management.
- Strong production engineering practices across automated testing, CI/CD, monitoring, incident response, and root-cause analysis.
- Demonstrated technical leadership through system design, hands-on implementation, code review, and mentorship.
- Ability to communicate technical decisions and tradeoffs clearly to engineering, research, product, and governance stakeholders.
PREFERRED QUALIFICATIONS
- Experience with Databricks or comparable cloud-based data and AI platforms for workflow orchestration, scalable processing, model deployment, and evaluation.
- Experience with NLP, text analytics, or large-scale processing of unstructured data.
- Experience building shared infrastructure for inference, evaluation, and model lifecycle management.
- Familiarity with retrieval-augmented generation, semantic search, and LLM orchestration frameworks.
- Experience with speech-to-text, speaker diarization, or processing conversational audio data.
- Experience deploying and operating cloud-native services on AWS or Azure.
- Experience with healthcare or other regulated environments, including sensitive data handling, auditability, and model governance.
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Press Ganey we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Additional Information for US based jobs:
Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well committed to a diverse workforce. We do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, and basis of disability or any other federal, state, or local protected class.
Pay Transparency Non-Discrimination Notice – Press Ganey will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
The expected base salary for this position ranges from $130,000 to $190,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus or commission tied to achieved results.
All your information will be kept confidential according to EEO guidelines.
Our privacy policy can be found here: https://www.pressganey.com/legal-privacy/
Company Description
Press Ganey is the leading experience measurement, data analytics, and insights provider for complex industries—a status we earned over decades of deep partnership with clients to help them understand and meet the needs of their key stakeholders. Our earliest roots are in U.S. healthcare – perhaps the most complex of all industries. Today we serve clients around the globe in every industry to help them improve the Human Experiences at the heart of their business. We serve our clients through an unparalleled offering that combines technology, data, and expertise to enable them to pinpoint and prioritize opportunities, accelerate improvement efforts and build lifetime loyalty among their customers and employees.
Like all great companies, our success is a function of our people and our culture. Our employees have world-class talent, a collaborative work ethic, and a passion for the work that have earned us trusted advisor status among the world’s most recognized brands. As a member of the team, you will help us create value for our clients, you will make us better through your contribution to the work and your voice in the process. Ours is a path of learning and continuous improvement; team efforts chart the course for corporate success.
Our Mission:
We empower organizations to deliver the best experiences. With industry expertise and technology, we turn data into insights that drive innovation and action.
Our Values:
To put Human Experience at the heart of organizations so every person can be seen and understood.
- Energize the customer relationship: Our clients are our partners. We make their goals our own, working side by side to turn challenges into solutions.
- Success starts with me: Personal ownership fuels collective success. We each play our part and empower our teammates to do the same.
- Commit to learning: Every win is a springboard. Every hurdle is a lesson. We use each experience as an opportunity to grow.
- Dare to innovate: We challenge the status quo with creativity and innovation as our true north.
- Better together: We check our egos at the door. We work together, so we win together.
Press Ganey is committed to providing reasonable accommodations to qualified individuals with disabilities or disabled veterans in the hiring process. If you need assistance or an accommodation to apply for a position online or for your interviews or assessments, please contact us at acommodations@pressganey.com. Please provide your contact information and the details of your request so we can best assist you.
ROLE AND RESPONSIBILITIES
We are seeking a Staff ML Engineer to lead the design, delivery, and operation of production-grade AI systems. You will build the services and high-throughput pipelines behind our text analytics platform and a growing portfolio of AI products, processing feedback and conversations from every channel our customers use to engage with patients and their customers. The central challenge is sustaining service reliability and measurable AI quality as models, inputs, and volumes change.
As a technical leader, you will guide engineers through design and implementation, contribute directly to the codebase, and lead architectural decisions across teams. Working primarily with Python and cloud-based data and AI platforms, with a growing emphasis on Databricks, you will shape the shared infrastructure supporting both established products and new AI applications.
- Own technical delivery from prototype through deployment and ongoing production support, partnering with AI Scientists and Product to define requirements, plan implementation, and resolve cross-team dependencies.
- Evaluate proposed AI solutions for production suitability, identify technical risks, and choose architectures that meet quality, reliability, and cost requirements without unnecessary complexity.
- Architect and build high-volume AI services and processing pipelines, including fault tolerance, backpressure, retries, idempotency, and recovery from partial failures.
- Lead the evolution of our Python services and Databricks-based platform for distributed processing, model serving, and integration of traditional ML and LLM-based components.
- Establish production engineering standards for automated testing, CI/CD, model and prompt versioning, load testing, controlled rollouts, and rollback.
- Build evaluation and monitoring capabilities to detect AI quality regressions and track service reliability, throughput, latency, and inference cost.
- Partner with Product and Responsible AI teams to define release criteria and implement requirements for model validation, data privacy, security, and governance.
- Optimize processing and inference workloads, balancing model quality, throughput, latency, capacity, and cost.
- Mentor engineers and lead architecture and code reviews, maintaining consistent standards for software quality and maintainability.
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Electrical Engineering, or a related technical discipline, or equivalent practical experience.
- 8+ years of professional software engineering experience, including at least 3 years owning ML or LLM systems in production and their operational support.
- Proven track record of independently leading complex technical initiatives from requirements through production, making architectural decisions and coordinating delivery across stakeholders.
- Advanced proficiency in Python for production services and data processing, with strong SQL skills.
- Experience designing and operating high-throughput distributed systems, with a strong understanding of failure recovery, multi-tenancy, and capacity planning.
- Hands-on experience deploying and operating LLM-based applications, including evaluation, output validation, observability, and cost management.
- Strong production engineering practices across automated testing, CI/CD, monitoring, incident response, and root-cause analysis.
- Demonstrated technical leadership through system design, hands-on implementation, code review, and mentorship.
- Ability to communicate technical decisions and tradeoffs clearly to engineering, research, product, and governance stakeholders.
PREFERRED QUALIFICATIONS
- Experience with Databricks or comparable cloud-based data and AI platforms for workflow orchestration, scalable processing, model deployment, and evaluation.
- Experience with NLP, text analytics, or large-scale processing of unstructured data.
- Experience building shared infrastructure for inference, evaluation, and model lifecycle management.
- Familiarity with retrieval-augmented generation, semantic search, and LLM orchestration frameworks.
- Experience with speech-to-text, speaker diarization, or processing conversational audio data.
- Experience deploying and operating cloud-native services on AWS or Azure.
- Experience with healthcare or other regulated environments, including sensitive data handling, auditability, and model governance.
Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Press Ganey we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
Additional Information for US based jobs:
Press Ganey Associates LLC is an Equal Employment Opportunity/Affirmative Action employer and well committed to a diverse workforce. We do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, and basis of disability or any other federal, state, or local protected class.
Pay Transparency Non-Discrimination Notice – Press Ganey will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
The expected base salary for this position ranges from $130,000 to $190,000. It is not typical for offers to be made at or near the top of the range. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also considered. In addition to base salary and a competitive benefits package, successful candidates are eligible to receive a discretionary bonus or commission tied to achieved results.
All your information will be kept confidential according to EEO guidelines.
Our privacy policy can be found here: https://www.pressganey.com/legal-privacy/
Machine Learning Job Roles in Washington DC
See all Machine Learning Jobs in Washington DC
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Search Machine Learning Jobs in Washington DCMachine Learning Jobs in Washington DC: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in Washington DC?
Federal contractors and technology consultancies are the most active sponsors in DC. Booz Allen Hamilton, Leidos, SAIC, Palantir, and Deloitte regularly file H-1B petitions for machine learning engineers and data scientists. Several AI-focused startups operating near the DC metro area also sponsor, particularly those with federal contracts or defense-related work. Sponsorship activity can be verified through DOL LCA disclosure data filtered to the DC area.
Which visa types are most common for machine learning roles in Washington DC?
The H-1B is the most common visa for machine learning roles in DC, as the field typically meets the specialty occupation standard given its degree requirements in computer science, mathematics, or a related field. The O-1A is an option for candidates with demonstrated exceptional ability, such as published research or notable industry recognition. Some roles at universities or nonprofits may qualify for cap-exempt H-1B petitions.
How to find machine learning visa sponsorship jobs in Washington DC?
Migrate Mate is built specifically for international job seekers and filters machine learning roles in Washington DC by visa sponsorship eligibility. Rather than sorting through thousands of listings manually, you can browse roles where employers have a documented history of sponsoring work visas. This is particularly useful in DC, where government contractor roles often have clearance requirements that affect sponsorship eligibility, and filtering by sponsorship history saves significant time.
Which areas in Washington DC have the most machine learning sponsorship jobs?
Most sponsored machine learning roles are concentrated in the DC metro area broadly, including Northern Virginia cities like Arlington, McLean, and Reston, which host major federal contractors and tech campuses. The District itself, particularly around K Street and Navy Yard, has growing AI and data science presence. Bethesda and the Maryland suburbs also have significant activity, especially near NIH-affiliated organizations and biotech employers.
Are there any DC-specific considerations for machine learning visa sponsorship?
Security clearances are a significant factor in DC's machine learning market. Many federal contractor roles require a clearance, which is generally not accessible to non-US citizens or permanent residents, effectively limiting which sponsored positions are open to international candidates. Candidates should focus on commercial, unclassified projects within larger contractors or on roles at organizations without clearance requirements. University-affiliated research positions at Georgetown or George Washington University may offer an alternative pathway with cap-exempt H-1B access.
What is the prevailing wage for sponsored machine learning jobs in Washington DC?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.