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Machine Learning Developer Jobs in Washington, DC

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

$125 - $150/hr

Role Summary The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties * Develop ...

SAIC

AI Machine Learning Developer Principal

Chantilly, VA · On-site +1

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance Required: TS.SCI Clearance Level Must Be Able to Obtain: None Potential for Remote Work:

New

SAIC

AI Machine Learning Developer Principal

Arlington, VA · On-site +1

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance Required: TS.SCI Clearance Level Must Be Able to Obtain: None Potential for Remote Work:

New

SAIC

AI Machine Learning Developer Principal

Chantilly, VA · On-site

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance Required: TS.SCI Clearance Level Must Be Able to Obtain: None Potential for Remote Work:

New

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

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All JobsMachine Learning Developer JobsMachine Learning Developer Jobs in Washington, DC

Machine Learning Developer information

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$43

$58

How much do machine learning developer jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for machine learning developer in Washington, DC is $43.35, according to ZipRecruiter salary data. Most workers in this role earn between $21.44 and $58.61 per hour, depending on experience, location, and employer.

What does a machine learning developer do?

A Machine Learning Developer designs, builds, and implements machine learning models and systems that enable computers to learn from data without explicit programming. They work with large datasets, select appropriate algorithms, and optimize models for various tasks such as predictions, classifications, and recommendations. Their responsibilities often include data preprocessing, feature engineering, model evaluation, and deploying models into production environments. Machine Learning Developers typically collaborate with data scientists, software engineers, and business teams to deliver AI-powered solutions.

What are the key skills and qualifications needed to thrive as a machine learning developer?

To excel as a Machine Learning Developer, you need a strong background in mathematics, statistics, programming (especially Python), and a relevant degree in computer science or related fields. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, as are certifications in data science or AI. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data findings into actionable solutions. These skills and qualities are essential to develop accurate models, collaborate with stakeholders, and drive innovation in a rapidly evolving field.

What are some common challenges faced by machine learning developers when deploying models to production environments?

Machine Learning Developers often encounter challenges such as ensuring model scalability, managing data drift, and integrating models with existing systems during deployment. Another frequent hurdle is monitoring model performance in real time and retraining models as new data becomes available. Collaborating closely with data engineers, DevOps, and software developers is essential to streamline the deployment pipeline and maintain model reliability in production.

What is the difference between Machine Learning Developer vs Data Scientist?

AspectMachine Learning DeveloperData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; certifications like TensorFlow or AWS MLBachelor's or Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops and deploys ML models in software or cloud environmentsAnalyzes data, builds models, and provides insights for decision-making
Industry UsageUsed in tech, finance, healthcare for deploying ML solutionsUsed across industries for data analysis, predictive modeling, and insights

Both roles require strong programming skills and knowledge of ML algorithms. Machine Learning Developers focus on building and deploying models in production environments, while Data Scientists analyze data to inform business decisions. The roles often overlap but differ mainly in their primary focus and end goals.

Is machine learning a high paying job?

Machine learning developers typically earn high salaries due to the specialized skills required, such as programming in Python or R and understanding algorithms. Salaries vary based on experience, location, and industry, but overall, the role is considered well-compensated within the tech field.

What are popular job titles related to Machine Learning Developer jobs in Washington, DC?

For Machine Learning Developer jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Machine Learning Developer jobs in Washington, DC look for?

The top searched job categories for Machine Learning Developer jobs in Washington, DC are:

Machine Learning Developer jobs near you
Infographic showing various Machine Learning Developer job openings in Washington, DC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $90,167 per year, or $43.3 per hour.

Artificial Intelligence / Machine Learning Developer

Unissant

Ashburn, VA • On-site

$127K - $190K/yr

Full-time

Re-posted 23 hours ago

Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent excited to join that effort. To learn more about our exciting organization, please visit us at .
We are seeking an Artificial Intelligence/Machine Learning Developer to join our team and support our federal customer.
Qualified applicants may be subject to a security investigation and must meet minimum qualifications for access to classified information. This is a highly technical position; individuals will be screened by peers in a technical review of skills and experience.
Essential Duties and Responsibilities:
  • Drive a big data approach to execute government requirements to manage, prepare, analyze, and enrich image, biometric, and related mission data to gather new insights.
  • As the AI/ML Developer, work as part of a team to provide consultative, architectural, program, and engineering support for a federal customer.
  • This is a client-facing position working on-site as per the requirements established by the DHS customer.
  • Develop, train, evaluate, fine-tune, and deploy advanced AI/ML, computer vision, deep-learning, and GenAI models.
  • Design and implement innovative AI solutions to address complex business challenges using techniques such as computer vision, image analysis, image classification, object detection, image segmentation, image matching, facial recognition, facial verification, biometric analysis, natural language processing, and large language models.
  • Prepare image, biometric, and related datasets for model development, including data extraction, cleaning, normalization, annotation, labeling, augmentation, feature engineering, data balancing, and training/validation/test-set construction.
  • Develop, train, evaluate, and improve image-analysis and computer-vision models used for biometric, identity-resolution, image-quality, matching, classification, detection, segmentation, or related mission capabilities.
  • Optimize model performance, ensuring accuracy, efficiency, scalability, bias awareness, and operational reliability.
  • Evaluate model performance using appropriate measures, including precision, recall, F1 score, confusion matrices, ROC-AUC, mean average precision, false-match rates, false-non-match rates, false acceptance rates, false rejection rates, latency, throughput, and related performance metrics.
  • Develop and maintain user-friendly AI applications and interfaces, including image-analysis tools, analytic dashboards, chatbots, virtual assistants, and generative content tools.
  • Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
  • Stay up to date with the latest advancements in AI/ML and emerging technologies, such as computer vision, biometrics, generative AI, reinforcement learning, and secure AI deployment.
  • Conduct research and experiments to explore new AI techniques and applications, including image-model training, computer-vision model evaluation, prompt engineering, advanced RAG, image retrieval, multimodal models, and fine-tuning LLMs.
  • Ensure compliance with data privacy, biometric-data handling, security, and governance requirements, especially when working with sensitive data, images, biometric information, and generative-AI outputs.
  • This role will be responsible for briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior levels of management.

Work Experience and Job Skills:
  • Three (3) or more years of experience in the Information Technology field focusing on AI/ML engineering projects, computer vision, image analysis, biometric technologies, MLOps, DevSecOps, and technical architecture.
  • Demonstrated hands-on experience developing, training, fine-tuning, evaluating, or deploying computer-vision, image-analysis, deep-learning, or biometric AI/ML models.
  • Experience working with image-analysis use cases such as image classification, object detection, image segmentation, image matching, face detection, facial recognition, facial verification, image quality assessment, liveness detection, identity verification, fingerprint analysis, iris recognition, or related technologies.
  • Familiarity with biometric systems, biometric matching, identity resolution, facial recognition, fingerprint, iris, liveness detection, or image-quality analysis is required.
  • Proficiency in developing, deploying, and fine-tuning generative-AI models, including large language models (LLMs).
  • Strong proficiency in programming languages such as Python, R, Java, and C/C++.
  • Experience with machine-learning, deep-learning, computer-vision, and generative-AI frameworks.
  • Proficiency in ML modeling frameworks and libraries such as scikit-learn, TensorFlow, Keras, PyTorch, OpenCV, YOLO, Detectron, Hugging Face, or equivalent platforms.
  • Experience with natural-language-processing techniques, including text classification and language generation.
  • Experience developing and evaluating image-analysis models using image transformations, feature extraction, embeddings, image-data augmentation, annotation/labeling, and model-performance metrics.
  • Solid understanding of any cloud platform, such as AWS, Azure, or GCP, and deployment strategies for AI/ML, image-analysis, and computer-vision workloads.
  • Solid understanding of MLOps and DevSecOps practices for deploying AI/ML, computer-vision, and image-analysis models and applications.
  • Proficiency in front-end development technologies such as React, Angular, Vue.js, HTML, CSS, and JavaScript.
  • Knowledge of database systems, such as SQL, NoSQL, vector databases, graph databases, and data-warehousing concepts.
  • An understanding and competency surrounding data storage, access, ingestion, and loading.
  • Databases: PostgreSQL, NoSQL, vector databases, graph databases, or comparable technologies.
  • ETL/ELT concepts.
  • Data warehouse concepts.
  • SQL.
  • Competency in data exploration, analytics, data quality, image-data processing, and feature engineering.
  • Python experience with Pandas, NumPy, Polars, PySpark, OpenCV, Pillow, scikit-image, or comparable data and image-processing tools.
  • Experience with Plotly, Matplotlib, or equivalent data-visualization tools.
  • Knowledge of data encoding, normalization, regularization, image preprocessing, data augmentation, and related data-preparation methods.
  • Understanding of deep-learning concepts and architectures such as CNNs, RNNs, LSTMs, GANs, transformers, vision transformers, and multimodal models, with the ability to apply them to real-world image, biometric, and mission datasets.
  • Proficiency in NLP tools such as SpaCy, Thinc, Gensim, or comparable frameworks.
  • Knowledge of GenAI tools, including Hugging Face models, OpenAI models, Grok, or comparable platforms.
  • General competency in various ML disciplines, including image classification, object detection, segmentation, facial recognition, biometric matching, forecasting, transformers, generative AI, anomaly detection, deep learning, and pattern recognition.
  • Enthusiastic, proactive, positive attitude with great listening skills, high integrity, and the ability to work effectively in a team environment.
  • Adaptability to changing priorities and a willingness to learn and grow are essential.
  • Excellent organizational skills and the ability to effectively manage concurrent projects.
  • Comprehensive problem-solving skills with exceptional attention to detail.
  • Ability to learn, evolve, think creatively, and work proactively.
  • Ability to work under pressure at times and to be extremely flexible with changing priorities.
  • Ability to work independently and in a team setting, take ownership of and complete relatively complex tasks, effectively using available resources, with minimal guidance.

Education:
Bachelor's Degree in Computer Science, Information Technology Management, Engineering, Data Science, Artificial Intelligence, Computer Vision, Mathematics, Statistics, Physics, or another related technical field is preferred. Alternative work-related experience, military duty, and/or specialized or higher education may be substituted.
Certificates, Licenses and Registrations:
This federal program requires candidates to be United States Citizens.
Must have an active DHS clearance.
Any related systems engineering, computer vision, biometrics, data science, machine learning, cloud, or technical certifications are desired.
AWS/Azure/GCP AI/ML certifications are preferred but not required.
Communication Skills:
Must have excellent written and verbal communication skills.
Ability to convey technical information-including model performance, image-analysis results, biometric matching limitations, and AI/ML solution tradeoffs-to non-technical individuals.
Demonstrated experience communicating effectively across internal and external organizations.
Must work well in a matrixed team environment.
Travel:
On-site in Ashburn, VA.
Environmental Requirements:
Mainly sedentary; in an office environment.
May be required to lift up to ten (10) pounds.
Flexible in working extended hours.
The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions.
Please note: Candidate(s) will be required to go through pre-employment screening.
Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets)

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