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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Get Access To All JobsHi, We're AppFolio
We're innovators, changemakers, and collaborators. We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do business. We're transforming Property Management; how property managers operate, how residents live, and how intelligence flows across an entire industry.
Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products, and a core layer delivering intelligent, high-impact experiences directly to our customers.
At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives—such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making.
Who We Are Looking For
We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio's production voice and chat agent pipelines, working at the intersection of LLM agent frameworks, real-time voice technology, and streaming infrastructure.
You will work with Product, Voice channel, and ML Platform teams to translate cutting-edge agent and voice research into reliable, low-latency, multi-channel experiences that scale across our entire customer base.
Your Impact
- Ship Voice & Text Agents: Architect and ship voice and text agent pipelines that handle real-time, multi-turn customer interactions.
- Reasoning vs. Latency: Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.
- Lead a Pod: Lead a small pod of ML and platform engineers; raise the bar on agent evaluation, observability, and incident response.
- Define Quality: Partner with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality.
- Optimize for Voice: Drive selective Small Language Model (SLM) fine-tuning and inference optimization for voice latency and cost.
Qualifications
You have shipped production AI agents serving real users in voice and/or text channels. You think in pipelines and systems, not just models. You move fast, deliver impact, and maintain sound engineering judgment. You are humble, collaborative, and low-ego, and you elevate those around you. You value work-life balance as a foundation for sustained high performance.
Must Have
- Agent frameworks: Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).
- Voice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands the trade-offs between end-to-end voice models and modular STT LLM TTS architectures.
- LLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.
- Telephony & cloud: Production experience with Twilio (or comparable telephony) and AWS.
- Engineering: Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.
- ML fundamentals: Solid foundation in deep learning, model evaluation, and inference optimization; able to deploy with Docker on AWS.
- Leadership: Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.
Nice to Have
- Experience fine-tuning Small Language Models for domain-specific voice applications.
- Familiarity with RAG over structured business data and tool-using agents over API surfaces.
- Prior experience in regulated or customer-facing industries with strict reliability requirements.
- Publicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.
Location
Find out more about our locations by visiting our site.
All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.
Compensation & Benefits
The compensation that we reasonably expect to pay for this role is: 167,200 - 209,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.
Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits - see here.
LI-KB1
Hi, We're AppFolio
We're innovators, changemakers, and collaborators. We're more than just a software company — we're building the AI-native platform where the real estate industry comes to do business. We're transforming Property Management; how property managers operate, how residents live, and how intelligence flows across an entire industry.
Realm-X is AppFolio's AI-native platform powering this transformation. It enables a new generation of intelligent capabilities across our products, including Realm-X Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X serves as both a foundation for internal teams to build and scale AI-powered products, and a core layer delivering intelligent, high-impact experiences directly to our customers.
At its core, Realm-X is built on a structured domain ontology and a set of shared business primitives—such as transactions, actions, reports, metrics, and skills—that enable AI systems to deeply understand and operate across the full context of property management workflows. This foundation allows us to build context-aware, action-oriented AI systems that go beyond simple assistance to power real automation and decision-making.
Who We Are Looking For
We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio's production voice and chat agent pipelines, working at the intersection of LLM agent frameworks, real-time voice technology, and streaming infrastructure.
You will work with Product, Voice channel, and ML Platform teams to translate cutting-edge agent and voice research into reliable, low-latency, multi-channel experiences that scale across our entire customer base.
Your Impact
- Ship Voice & Text Agents: Architect and ship voice and text agent pipelines that handle real-time, multi-turn customer interactions.
- Reasoning vs. Latency: Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.
- Lead a Pod: Lead a small pod of ML and platform engineers; raise the bar on agent evaluation, observability, and incident response.
- Define Quality: Partner with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality.
- Optimize for Voice: Drive selective Small Language Model (SLM) fine-tuning and inference optimization for voice latency and cost.
Qualifications
You have shipped production AI agents serving real users in voice and/or text channels. You think in pipelines and systems, not just models. You move fast, deliver impact, and maintain sound engineering judgment. You are humble, collaborative, and low-ego, and you elevate those around you. You value work-life balance as a foundation for sustained high performance.
Must Have
- Agent frameworks: Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).
- Voice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands the trade-offs between end-to-end voice models and modular STT LLM TTS architectures.
- LLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.
- Telephony & cloud: Production experience with Twilio (or comparable telephony) and AWS.
- Engineering: Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.
- ML fundamentals: Solid foundation in deep learning, model evaluation, and inference optimization; able to deploy with Docker on AWS.
- Leadership: Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.
Nice to Have
- Experience fine-tuning Small Language Models for domain-specific voice applications.
- Familiarity with RAG over structured business data and tool-using agents over API surfaces.
- Prior experience in regulated or customer-facing industries with strict reliability requirements.
- Publicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.
Location
Find out more about our locations by visiting our site.
All late-stage candidates complete an in-person meeting with an AppFolian as part of our hiring process.
Compensation & Benefits
The compensation that we reasonably expect to pay for this role is: 167,200 - 209,000 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.
Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits - see here.
LI-KB1
Machine Learning Job Roles 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.