Machine Learning Intern Jobs in District of Columbia
Machine Learning Intern jobs in District of Columbia draw strong demand from a market anchored in federal agencies, defense contractors, and policy-driven research institutions, with openings at every level from first-year undergraduates to advanced doctoral candidates. Washington, D.C. is the dominant hiring hub, with activity extending into nearby corridors, and established employers like Booz Allen Hamilton, Leidos, and the Mitre Corporation regularly take on machine learning interns across natural language processing, computer vision, and data pipeline development. Roles often center on applied research with national security, public health, or policy analytics applications. See the openings below and apply to the ones that match your experience.
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Showing 5 of 6+ Machine Learning Intern jobs
At Atlassian, we’re on a mission to unleash the potential of every team. As part of that mission, we're investing deeply in Generative AI — pioneering advanced modeling and rapid innovations that accelerate how teams work, discover, and create.
We’re seeking a Principal Machine Learning Systems Engineer (P60) to lead technical directions of GenAI Products & Knowledge Innovations in US. You’ll focus on building and scaling the systems that power advanced GenAI products with enterprise knowledge, rapid prototyping, and applied research—bridging cutting-edge algorithms with reliable, high-performance infrastructure.
Working at Atlassian
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Responsibilities:What You'll Do
Design and Build ML Systems
Architect and implement scalable systems for training, fine-tuning, and serving large language models and embeddings.
Build efficient retrieval, hybrid search, and RAG pipelines integrated with knowledge-grounded data.
Develop tools and infra to support rapid experimentation, evaluation, and deployment of prototypes.
- Enable Rapid Prototyping & Applied Research
Partner with applied scientists to bring new ideas to life in robust, production-ready pipelines.
Build proof-of-concept (POC) systems and evolve them into reliable, scalable services.
Optimize latency, throughput, and resource efficiency for GenAI workloads.
Collaborate Across Disciplines
Work closely with ML engineers, backend developers, and product teams to ship end-to-end innovations.
Contribute to best practices in model deployment, monitoring, and evaluation.
Help establish the team as a world-class hub for GenAI systems innovation.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges:In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $236,700 - $309,025
Zone B: $213,030 - $278,123
Zone C: $196,461 - $256,491
Qualifications:What We're Looking For
✅ Experience
6+ years in ML systems engineering, backend engineering, or infrastructure roles.
Strong track record of building and scaling ML-powered services in production.
Experience with large-scale model training, inference pipelines, or search/retrieval systems.
Skills
Proficiency in backend systems and ML frameworks (Python, PyTorch, TensorFlow, Hugging Face).
Experience with vector databases (Weaviate, Pinecone, FAISS), orchestration frameworks (LangChain, LlamaIndex).
Strong coding skills and ability to optimize systems for performance and reliability.
Familiarity with cloud environments (AWS, GCP, Azure) and container/orchestration tools (Kubernetes, Docker).
Education
Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent industry experience.
Nice to Have
Background in distributed systems, high-performance computing, or GPU optimization.
Familiarity with search/GenAI evaluation metrics (e.g., NDCG, groundedness, latency benchmarks).
Experience with monitoring, observability, and reliability practices for ML systems.
Contributions to open-source infra or ML systems frameworks.
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh.
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
At Atlassian, we’re on a mission to unleash the potential of every team. As part of that mission, we're investing deeply in Generative AI — pioneering advanced modeling and rapid innovations that accelerate how teams work, discover, and create.
We’re seeking a Principal Machine Learning Systems Engineer (P60) to lead technical directions of GenAI Products & Knowledge Innovations in US. You’ll focus on building and scaling the systems that power advanced GenAI products with enterprise knowledge, rapid prototyping, and applied research—bridging cutting-edge algorithms with reliable, high-performance infrastructure.
Working at Atlassian
Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity.
Responsibilities:What You'll Do
Design and Build ML Systems
Architect and implement scalable systems for training, fine-tuning, and serving large language models and embeddings.
Build efficient retrieval, hybrid search, and RAG pipelines integrated with knowledge-grounded data.
Develop tools and infra to support rapid experimentation, evaluation, and deployment of prototypes.
- Enable Rapid Prototyping & Applied Research
Partner with applied scientists to bring new ideas to life in robust, production-ready pipelines.
Build proof-of-concept (POC) systems and evolve them into reliable, scalable services.
Optimize latency, throughput, and resource efficiency for GenAI workloads.
Collaborate Across Disciplines
Work closely with ML engineers, backend developers, and product teams to ship end-to-end innovations.
Contribute to best practices in model deployment, monitoring, and evaluation.
Help establish the team as a world-class hub for GenAI systems innovation.
At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. We follow consistent hiring practices and account for each candidate's skills, knowledge, and experience when setting base pay within the range.
Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter.
This role may also be eligible for benefits, bonuses, commissions, and equity.
Pay Ranges:In The United States, we have three geographic pay zones. For this role, our current base pay ranges for new hires in each zone are:
Zone A: $236,700 - $309,025
Zone B: $213,030 - $278,123
Zone C: $196,461 - $256,491
Qualifications:What We're Looking For
✅ Experience
6+ years in ML systems engineering, backend engineering, or infrastructure roles.
Strong track record of building and scaling ML-powered services in production.
Experience with large-scale model training, inference pipelines, or search/retrieval systems.
Skills
Proficiency in backend systems and ML frameworks (Python, PyTorch, TensorFlow, Hugging Face).
Experience with vector databases (Weaviate, Pinecone, FAISS), orchestration frameworks (LangChain, LlamaIndex).
Strong coding skills and ability to optimize systems for performance and reliability.
Familiarity with cloud environments (AWS, GCP, Azure) and container/orchestration tools (Kubernetes, Docker).
Education
Bachelor’s or Master’s in Computer Science, Machine Learning, or related field—or equivalent industry experience.
Nice to Have
Background in distributed systems, high-performance computing, or GPU optimization.
Familiarity with search/GenAI evaluation metrics (e.g., NDCG, groundedness, latency benchmarks).
Experience with monitoring, observability, and reliability practices for ML systems.
Contributions to open-source infra or ML systems frameworks.
Benefits & Perks
Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.
About Atlassian
At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.
We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.
To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.
To learn more about our culture and hiring process, visit go.atlassian.com/crh.
In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.
See All 6 Machine Learning Intern Jobs in District of Columbia
Find roles in District of Columbia that match your experience and apply in just a few clicks.
Find Machine Learning Intern JobsMachine Learning Intern Jobs by City in District of Columbia
Where District of Columbia roles are concentrated, by current openings.
Machine Learning Intern Job Market in District of Columbia
A snapshot from current District of Columbia openings, updated as new roles post.
Who's Hiring
What District of Columbia Employers Look For
The qualifications that appear most often in machine learning intern jobs across District of Columbia.
- Currently enrolled in a bachelor's or master's degree program in computer science or related field
- Hands-on experience with Python and core machine learning libraries such as TensorFlow or PyTorch
- Ability to obtain and maintain a U.S. government security clearance or eligibility
- Familiarity with data preprocessing, model training, and evaluation on real-world datasets
- Experience applying machine learning methods to structured or unstructured data in a project context
- Strong written and verbal communication skills for documenting and presenting technical findings
Machine Learning Intern Jobs in District of Columbia: Frequently Asked Questions
How do you become a machine learning intern in District of Columbia?
Machine learning intern roles in District of Columbia do not require a state-issued license, but most positions require active enrollment in a bachelor's or graduate program in computer science, data science, or engineering. Because many D.C.-area employers are federal contractors, candidates who can demonstrate clearance eligibility gain a significant edge. A portfolio showing applied projects using Python-based frameworks, presented through coursework or independent work, is the most direct path to landing interviews with area employers.
Which companies hire machine learning interns in District of Columbia?
Employers hiring machine learning interns in District of Columbia right now include Crowe, AppFolio, and Atlassian, based on current listings on Migrate Mate as of September 2026. The D.C. market is heavily shaped by federal contracting firms and research-focused organizations that staff internship pipelines year-round to support government-facing analytics and AI projects.
Which District of Columbia cities have the most machine learning intern jobs?
Washington account for the most machine learning intern openings in District of Columbia. Washington, D.C. itself drives the bulk of postings because the city is home to the headquarters of major federal agencies and the large defense and consulting contractors that serve them, while nearby suburban areas benefit from the same employer base spreading into Virginia and Maryland corridors.
Are there remote machine learning intern jobs in District of Columbia?
Yes, and they are more common than in many other intern roles, though a meaningful share of D.C.-area positions still require on-site work due to clearance or data-handling requirements. About 100% of machine learning intern openings tied to District of Columbia are remote or hybrid as of September 2026, reflecting the desk-based and analytical nature of the work. Roles focused on model development and data analysis tend to be the most flexible, while those involving classified systems or sensitive government data almost always require physical presence.
How can I get hired as a machine learning intern in District of Columbia with little or no experience?
The most realistic entry path is applying to structured internship cohort programs that large D.C.-area federal contractors such as Booz Allen Hamilton, SAIC, and Leidos run specifically for students without prior industry experience. These programs pair interns with mentors on government-sponsored AI projects and do not require a prior internship record. Candidates who strengthen their applications with completed Kaggle projects, GitHub repositories demonstrating Python proficiency, and any coursework in statistics or linear algebra are consistently more competitive for these cohort slots than those relying on GPA alone.
Where can I find and apply to machine learning intern jobs in District of Columbia?
You can find and apply to machine learning intern jobs in District of Columbia on Migrate Mate, which lists current openings in the area. Search the listings to find roles that fit your background and apply directly to the ones that match your experience and availability.
See All 6 Machine Learning Intern Jobs in District of Columbia
Find roles in District of Columbia that match your experience and apply in just a few clicks.
Find Machine Learning Intern Jobs