Machine Learning Engineer Visa Sponsorship Jobs in Washington DC
Washington DC's machine learning engineer job market is anchored by federal agencies, defense contractors, and policy-adjacent tech firms. Employers like Booz Allen Hamilton, Leidos, Palantir, and Amazon Web Services actively hire ML engineers here, many of whom require H-1B visa or O-1 visa sponsorship. Security clearance compatibility and government contract work shape hiring in ways distinct from other major tech markets.
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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 Engineer Job Roles in Washington DC
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Search Machine Learning Engineer Jobs in Washington DCMachine Learning Engineer Jobs in Washington DC: Frequently Asked Questions
Which companies sponsor visas for machine learning engineers in Washington DC?
Booz Allen Hamilton, Leidos, SAIC, Palantir, and Amazon Web Services are among the more active sponsors for machine learning engineers in the DC area. Federal consulting firms dominate the local market, so many ML roles are tied to government contracts. Large technology companies with DC offices, including Microsoft and Google, also file H-1B petitions for ML engineers in this region regularly.
Which visa types are most common for machine learning engineer roles in Washington DC?
The H-1B is the most common visa for machine learning engineers in Washington DC, as the role consistently qualifies as a specialty occupation requiring at least a bachelor's degree in computer science, mathematics, or a related field. Candidates with exceptional recognition may pursue the O-1A. Some employer-sponsored green card pathways, particularly EB-2 and EB-3, are also used by DC-area employers for established ML engineers.
How to find machine learning engineer visa sponsorship jobs in Washington DC?
Migrate Mate filters machine learning engineer jobs specifically by visa sponsorship and location, making it straightforward to identify DC-area employers who are open to sponsoring. Because Washington DC's ML market is heavily tied to government contracting, it helps to look for roles that explicitly list H-1B sponsorship and do not require active security clearances, as those positions are generally not available to visa holders.
Which areas in Washington DC have the most machine learning engineer sponsorship jobs?
Most ML engineering sponsorship activity in the DC metro area is concentrated in DC proper, Bethesda, McLean, and Arlington in Northern Virginia. The Northern Virginia corridor, sometimes called the DMV tech corridor, hosts major data center infrastructure and defense tech firms. Bethesda and Rockville in Maryland are also notable, particularly for ML roles adjacent to health research institutions like the NIH.
Are there any DC-specific considerations for machine learning engineers seeking visa sponsorship?
Washington DC's ML hiring is uniquely shaped by federal contracting. Many roles require or prefer U.S. citizenship or security clearances, which are unavailable to most visa holders, so it is important to identify roles at agencies or contractors that explicitly sponsor and do not have clearance prerequisites. Universities like Georgetown and George Washington also produce ML talent pipelines that influence how DC employers approach OPT and H-1B hiring.
What is the prevailing wage for sponsored machine learning engineer 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.