Junior AI/ML Engineer
Herndon, VA · Hybrid
Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver ...
Junior AI/ML Engineer
Herndon, VA · Hybrid
Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver ...
Junior AI/ML Engineer
Herndon, VA · On-site
Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver ...
Quick apply
Junior AI/ML Engineer
Herndon, VA · On-site
Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver ...
AI Developer - Model Creation & Full Stack with Security Clearance
Hampton, VA · On-site
$150K - $175K/yr
Everforth ECS is seeking a highly skilled AI Developer with expertise in machine learning model ... Integrate AI models into web and mobile applications. Ensure scalability, security, and performance ...
AI Developer - Model Creation & Full Stack with Security Clearance
Hampton, VA · On-site
$150K - $175K/yr
Everforth ECS is seeking a highly skilled AI Developer with expertise in machine learning model ... Integrate AI models into web and mobile applications. Ensure scalability, security, and performance ...
Creating machine learning models that conduct text classification and topic modeling in Python ... Apply now with our easy 3-minute, mobile-friendly initial application process. Your future starts ...
Creating machine learning models that conduct text classification and topic modeling in Python ... Apply now with our easy 3-minute, mobile-friendly initial application process. Your future starts ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... and mobile applications, leveraging our high-scale ML models. Our core mission involves ... Build machine learning models through all phases of development, from design through training ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
... mobile app. We partner with product, tech and design teams to deliver app features that delight ... Build machine learning and NLP models through all phases of development, from design through ...
Mobile Machine Learning information
See Virginia salary details
$15.04 is the 25th percentile. Wages below this are outliers.
$12.15 - $21.82
84% of jobs
$21.82 - $31.48
16% of jobs
$31.48 - $41.14
0% of jobs
$41.14 - $50.81
0% of jobs
$50.81 - $60.47
0% of jobs
$60.47 - $70.13
0% of jobs
$70.13 - $79.79
0% of jobs
$79.79 - $89.46
0% of jobs
$89.46 - $99.12
0% of jobs
$99.12 - $108.78
0% of jobs
$108.78 - $118.45
0% of jobs
$12
$25
$118
How much do mobile machine learning jobs pay per hour?
As of Jun 23, 2026, the average hourly pay for mobile machine learning in Virginia is $25.11, according to ZipRecruiter salary data. Most workers in this role earn between $14.28 and $20.00 per hour, depending on experience, location, and employer.
What are the key skills and qualifications needed to thrive as a Mobile Machine Learning Engineer, and why are they important?
To thrive as a Mobile Machine Learning Engineer, you need a solid background in computer science, machine learning, and mobile application development, often supported by a relevant degree and experience. Proficiency with ML frameworks (like TensorFlow Lite or Core ML), mobile platforms (Android/iOS), and deployment tools is typically required. Strong problem-solving skills, adaptability, and effective communication set standout professionals apart in this field. These skills are crucial for successfully developing, optimizing, and integrating machine learning models into efficient and user-friendly mobile applications.
What is mobile machine learning?
Mobile machine learning refers to the development and deployment of machine learning models on mobile devices such as smartphones and tablets. It enables apps to perform tasks like image recognition, language translation, and speech processing directly on the device without needing to send data to the cloud. This approach improves privacy, reduces latency, and can work even without an internet connection. Developers use frameworks like TensorFlow Lite, Core ML, and PyTorch Mobile to optimize models for the limited resources of mobile hardware.
What is the difference between Mobile Machine Learning vs Data Scientist?
| Aspect | Mobile Machine Learning | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's in CS, ML, or related; experience with mobile platforms | Bachelor's or higher in CS, Statistics, or related; data analysis skills |
| Work Environment | Mobile app development teams, on-device processing | Data analysis teams, research environments |
| Industry Usage | Mobile app companies, tech startups | Finance, healthcare, tech firms |
| Common Search/Comparison | Yes | Yes |
Mobile Machine Learning focuses on developing ML models optimized for mobile devices and integrating them into mobile apps. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming and ML knowledge, Mobile Machine Learning emphasizes on-device deployment and mobile platform expertise, whereas Data Scientists focus on data analysis and model development for broader applications.
What are some common challenges faced by Mobile Machine Learning engineers when deploying models on mobile devices?
Mobile Machine Learning engineers often encounter challenges related to limited computational resources and memory constraints on mobile devices. Optimizing models for efficient inference without significant loss in accuracy is a key hurdle, as is ensuring compatibility across different devices and operating systems. Additionally, balancing power consumption and real-time performance is critical, so engineers frequently collaborate with mobile app developers and hardware specialists to deliver seamless user experiences while maintaining model integrity.
What are the most commonly searched types of Machine Learning jobs in Virginia? The most popular types of Machine Learning jobs in Virginia are:
What are popular job titles related to Mobile Machine Learning jobs in Virginia? For Mobile Machine Learning jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Mobile Machine Learning jobs in Virginia look for? The top searched job categories for Mobile Machine Learning jobs in Virginia are:
- Remote Shrink Wrap Machine Operator
- Machine Learning Object Detection
- Cnc Operator Machine Operator
- Take Off Operator
- Medical Machine Learning
- Aide Blister Packing Machine Operator
- Afternoon Shrink Wrap Machine Operator
- From Home Capsule Filling Machine Operator
- Day Shift Pcl Canada
- Freelance Rotogravure Printing Machine Operator
What cities in Virginia are hiring for Mobile Machine Learning jobs? Cities in Virginia with the most Mobile Machine Learning job openings:
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 8 days ago
Job description
Junior AI/ML Engineer
Location: Herndon, VA (Hybrid Work)
Preferred: US Citizenship
Node.Digital is an innovative solutions development company that combines agile development services with next-generation technologies in Cloud, Mobile, and AI/Machine Learning. We deliver state-of-the-art enterprise solutions to both government and commercial clients. We are looking for talented people to join our efforts to enable digitalization of organizations with AI Automation and Machine Learning.
Key Responsibilities:
Support data preprocessing and feature engineering pipelines under senior engineer direction: clean, normalize, and validate HRSA fraud-related datasets; handle class imbalance preparation (SMOTE, undersampling) and train/validation/test split management.
Assist in the development, training, and evaluation of supervised fraud classification models; compute and document standard evaluation metrics (accuracy, precision, recall, F1 score, AUC-ROC, confusion matrices) for government review in EPLC-required model evaluation reports.
Maintain and monitor ML experiment tracking using MLflow or equivalent tooling approved for the IRMS environment; log hyperparameter configurations, training runs, and evaluation results with full reproducibility documentation.
Support model drift detection and retraining pipelines: run scheduled evaluation jobs, flag performance degradation against established baselines, and escalate findings to the AI/ML Lead Engineer and Fraud AI/ML SME.
Assist the NLP/NER pipeline team (Rohit) with data transformation tasks: format-convert NER pipeline outputs into feature-compatible schemas for downstream ML models; validate entity extraction quality against labeled reference sets.
Develop and maintain Jupyter notebook-based model exploration and reporting artifacts for use in EPLC deliverables, sprint reviews, and government demonstrations.
Support UiPath Maestro agent integration testing: prepare model inference payloads, validate agent input/output schemas, and assist with integration testing between ML model inference APIs and the persona-based agent layer.
Implement and maintain data pipeline scripts (Python/Pandas/NumPy) for batch data ingestion, feature store updates, and model scoring batch runs within the IRMS security boundary.
Follow and enforce IRMS boundary data handling procedures: ensure no PII/PHI is processed outside approved environments; maintain developer/test environment segregation per HHS security policy.
Produce supporting artifacts for EPLC deliverables: training data specifications, model evaluation appendices, data dictionary updates, and sprint retrospective documentation as directed by the PM and AI/ML Lead.
Participate in code reviews; adhere to OWASP secure coding standards, NIST SP 800-160 engineering principles, and Node's internal CI/CD quality gates.
Requirements
Required Skills:
Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, or a closely related field; recent graduates with strong applied ML coursework or project portfolios will be considered.
1-3 years of hands-on experience (including internships, graduate research, or project work) in machine learning, data science, or data engineering with Python.
Proficiency in Python ML stack: scikit-learn, Pandas, NumPy; familiarity with at least one deep learning framework (TensorFlow or PyTorch) for model evaluation and inference tasks.
Demonstrated experience with standard ML evaluation workflows: train/validation/test split design, cross-validation, metric computation, and results documentation.
Experience with Jupyter notebooks for data exploration, model evaluation, and technical reporting.
Familiarity with Git-based version control and CI/CD principles; ability to work within a structured sprint cadence with documented deliverable commitments.
Demonstrated ability to handle sensitive data responsibly; understanding of data governance, access control, and the importance of environment segregation in a regulated or government setting.
Strong written communication skills: ability to produce clear, organized technical documentation suitable for government review.
Benefits
- Medical
- Dental
- Vision
- Basic Life
- Health Saving Account
- 401K Matching
- Three weeks of PTO/Sick
- 11 Paid Holidays
- Pre-Approved Online Training
About Node.Digital
Sourced by ZipRecruiter
Industry
Software development
Company size
11 - 50 Employees
Headquarters location
Leesburg, VA, US
Year founded
2017