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Freelance Audio Machine Learning Jobs in Silver Spring, MD

10a Labs

Engineering Fellowship

Washington, DC · On-site

... Machine Learning Engineering: * * Computer vision skills (OCR, image classification, deep fake detection) * Familiarity with multimodal learning (text-image or text-audio) or cross-domain model ...

TechWish

Lead AI Engineer

Rockville, MD · On-site

$80/hr

Document ingestion (PDF, HTML, images, video/audio) * Multimodal extraction (OCR, layout parsing ... AI / Machine Learning * Strong expertise in: * NLP and large language models (LLMs) * Retrieval ...

New

Assured Consulting Solutions

AI/ML Engineer

Reston, VA · On-site

$175K - $220K/yr

... images, audio, and documents. Our AI/ML Engineer is the core mission specialist who develops ... Design, implement, and optimize machine learning models for new mission-critical use cases and ...

Howard University

Research Assistant

Washington, DC · On-site

$21 - $31/hr

... creating audio captcha technology. The candidate should be well-informed about the scientific ... in machine learning and data science; advanced degrees may offset experience requirements ...

CaseGuard

Senior Software Engineer - C# / WPF

Arlington, VA · On-site

$140K - $185K/yr

Experience with video/audio programming, including FFmpeg or similar technologies, codecs and containers, frame-accurate playback, and hardware acceleration. * Experience integrating machine learning ...

CaseGuard

Senior Software Engineer - C# / WPF

Arlington, VA · On-site

$140K - $185K/yr

Experience with video/audio programming, including FFmpeg or similar technologies, codecs and containers, frame-accurate playback, and hardware acceleration. * Experience integrating machine learning ...

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Showing results 21-40

All JobsAudio Machine Learning JobsFreelance Audio Machine Learning JobsFreelance Audio Machine Learning Jobs in Silver Spring, MD

Freelance Audio Machine Learning information

See Silver Spring, MD salary details

$66.2K

$72.4K

$77K

How much do freelance audio machine learning jobs pay per year?

As of Aug 7, 2026, the average yearly pay for freelance audio machine learning in Silver Spring, MD is $72,364.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,800.00 and $74,900.00 per year, depending on experience, location, and employer.

What is the difference between Freelance Audio Machine Learning vs Freelance Audio Signal Processing?

AspectFreelance Audio Machine LearningFreelance Audio Signal Processing
Required SkillsMachine learning, programming, audio analysisDigital signal processing, audio engineering, software tools
Work EnvironmentData analysis, model development, algorithm designAudio editing, filtering, signal enhancement
Common EmployersTech companies, startups, research labsAudio production houses, broadcasting, music industry
CertificationsMachine learning, data science, programming certificationsAudio engineering, DSP certifications

Freelance Audio Machine Learning focuses on developing algorithms and models to analyze and interpret audio data using machine learning techniques. In contrast, Freelance Audio Signal Processing involves applying traditional digital signal processing methods to enhance or modify audio signals. Both roles require technical expertise but differ in their core methods and applications.

What are popular job titles related to Freelance Audio Machine Learning jobs in Silver Spring, MD? For Freelance Audio Machine Learning jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Freelance Audio Machine Learning jobs in Silver Spring, MD look for? The top searched job categories for Freelance Audio Machine Learning jobs in Silver Spring, MD are:
Freelance Audio Machine Learning jobs near you

Engineering Fellowship

10a Labs

Washington, DC • On-site

Full-time

Re-posted 10 days ago

Job description

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.
About the role: As an Engineering Fellow, you will apply your technical skills to support high-impact research problems. Fellows will contribute across the project lifecycle - from processing diverse data sources and designing dynamic visualizations, to deploying sophisticated models and building cloud infrastructure. This is a hands-on role at the intersection of applied research and practical engineering, with opportunities to explore novel methods, test ideas quickly, and generate insights.
Fellows specialize in one of three concentrations based on interest and past experience: Software Engineering, Data Engineering, or Machine Learning.
In this role, you will:
  • Collaborate with engineers on real projects, including client-facing products and in-house tooling;
  • Assist with researching experiment design and automation, particularly as it relates to abuse detection or red teaming of AI systems;
  • Ideate / brainstorm new research approaches to known and novel problems in the Trust & Safety and AI Security fields; and
  • Support other critical initiatives.

Software Engineering concentration responsibilities may include:
  • Implementing cloud infrastructure for deploying machine learning models;
  • Writing high-coverage test suites for complex codebases; and
  • Guiding project development with software engineering best practices, including version control, continuous integration, and design patterns.

Data Engineering concentration responsibilities may include:
  • Sourcing, curating, and processing diverse data sources across domains and modalities, including automated collection of internet-scale datasets;
  • Designing data architecture schemata, implementing with production-grade data storage tools, and interfacing via custom APIs; and
  • Developing front-end dashboards and other visualizations.

Machine Learning concentration responsibilities may include:
  • Training, validating, evaluating, and deploying cutting-edge machine learning algorithms including classifiers, LLMs, and computer vision models;
  • Building agentic systems for automated prompting, red-teaming, research, and rapid experimentation;
  • Supporting projects with specialized knowledge of frontier model architectures and cutting-edge technology.

We're looking for someone who:
  • Brings curiosity and creativity to ambiguous research problems, with a bias toward experimentation and rapid iteration;
  • Thrives in collaborative, interdisciplinary environments; is resourceful, proactive, and adaptable;
  • Is comfortable communicating technical ideas clearly to both technical and non-technical audiences; and
  • Is excited about contributing to real-world applications and exploring new methods that push beyond standard benchmarks.

Requirements:
  • Strong academic background and quantitative foundation demonstrated through applied coursework, research, or hands-on-experience
  • Strong Python background
  • Clear communicator of technical concepts for non-technical audiences

Nice to have:
  • Familiarity with Google Cloud Platform (or similar), including storage and database services (e.g., Cloud Storage, CloudSQL, Cloud Spanner), workflow orchestration (e.g., Cloud Composer/Airflow, Cloud Run, Pub/Sub), and ML services (e.g., Vertex AI, Compute Engine)
  • Experience managing full lifecycle projects from design to deployment

Software Engineering:
    • Experience designing and building end-to-end backend systems, from architecture and data modeling to deployment, scaling, and monitoring
    • Proficiency in backend programming languages such as Python, Java, Kotlin, Node.js, or Go and experience building secure systems, APIs, and microservices
    • Knowledge of security best practices, including authentication methods (OAuth, JWT), encryption, and secure API development; knowledge of common attack vectors (SQL injection, privilege escalation, DDoS) and effective mitigation strategies

Data Engineering:
    • Experience with web scraping/crawling (e.g., Beautiful Soup, Selenium, Scrapy)

Machine Learning Engineering:
    • Computer vision skills (OCR, image classification, deep fake detection)
    • Familiarity with multimodal learning (text-image or text-audio) or cross-domain model evaluation
    • Exposure to MLOps tools and practices (Docker, Kubernetes, CI/CD for ML, MLflow, etc.)
    • Understanding of modern retrieval-augmented generation (RAG), AI agent frameworks, and context-aware orchestration (e.g., LangChain, LlamaIndex, OpenAI Agents, or AutoGen) for building intelligent applications

Benefits:
  • Flexible start / end dates
  • Remote work (based in the continentalU.S.)
  • Flexible schedule, up to 20 hours per week (negotiable)
  • Hourly pay commensurate with experience and qualifications
    • $30 per hour for undergraduate students
    • $35 per hour for graduate students
    • $50 per hour for advanced PhD students
    • $60 per hour for postdocs or non-tenured positions
    • $125 per hour for tenure-track academics

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