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Audio Machine Learning Jobs in Washington (NOW HIRING)

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE ...

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

... images, video, metadata, audio, and text, and we recognize the need for robust, affordable ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA · On-site

$90K - $210K/yr

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE ...

Familiarity with applied machine learning domains (e.g., natural language processing, computer vision, autonomy, audio analysis) * Experience and knowledge in cybersecurity best practices

... 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 ...

... 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 ...

Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters ... speech/audio, and LLM-based systems * Build and maintain CI/CD workflows for ML services, model ...

Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters ... speech/audio, and LLM-based systems * Build and maintain CI/CD workflows for ML services, model ...

Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters ... speech/audio, and LLM-based systems * Build and maintain CI/CD workflows for ML services, model ...

Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters ... speech/audio, and LLM-based systems * Build and maintain CI/CD workflows for ML services, model ...

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Showing results 1-20

Audio Machine Learning information

See Washington salary details

$33.4K

$95.7K

$194.2K

How much do audio machine learning jobs pay per year?

As of May 30, 2026, the average yearly pay for audio machine learning in Washington is $95,654.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,600.00 and $128,000.00 per year, depending on experience, location, and employer.

What is an Audio Machine Learning job?

An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.

What are the key skills and qualifications needed to thrive in the Audio Machine Learning position, and why are they important?

To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.

What are the typical daily responsibilities of someone working in Audio Machine Learning?

Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.
What are the most commonly searched types of Audio Machine Learning jobs in Washington? The most popular types of Audio Machine Learning jobs in Washington are:
What are popular job titles related to Audio Machine Learning jobs in Washington? For Audio Machine Learning jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Audio Machine Learning jobs? Cities in Washington with the most Audio Machine Learning job openings:
Machine Learning Engineer

Machine Learning Engineer

MORSE Corp

Arlington, VA • On-site

Other

Posted 24 days ago


Job description

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role in designing, implementing, and managing complex ML algorithms and systems, with a focus on computer vision (CV) and other types of data. You will be responsible for acquiring truth data, integrating algorithms, testing algorithms, combining algorithms, reviewing literature to stay on top of the latest-and-greatest methods, analyzing data from field tests, and developing advanced algorithms. MORSE's AI & ML work crosses modalities, and experience or interest in the fields of Large Language Models (LLM), audio analysis, computer vision, and advanced reasoning is a plus. You will work with MORSE's current team of engineers to transition algorithms to production, which may run on on-prem servers, on the cloud, or on a real-time embedded system. You will be part of our team working to accelerate our US National Security customers abilities to use natural language processing capabilities in mission-critical environments. 

Responsibilities: 
  • Develop, fine-tune, train, and optimize Computer Vision algorithms processing tasks such as object detection and tracking.  
  • Use MLOps tools for efficient experiment tracking, data management, and reproducibility 
  • Write robust, efficient, and maintainable code 
  • Track the latest advancements with machine learning research to bring new techniques and methodologies to MORSE 
  • Conduct experiments and perform rigorous evaluations to assess the effectiveness and efficiency of CV models 

Skills and Requirements: 
  • US CITIZENSHIP REQUIRED and the ability to obtain a U.S. Security Clearance 
  • Masters or Ph.D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or related field 
  • Proven experience in applying CV models, techniques, frameworks, and libraries to implement and fine-tune models 
  • Proven experience testing and validating the performance of AI technologies in real-world applications 
  • Proficiency in Python 
  • Experience with cloud platforms (AWS and Azure) 
  • Experience with Docker 
  • Experience with MLOps tools such as Airflow, MLFlow, AimStack, etc. 
  • Exceptional communication skills and the ability to work well with customers 
  • Understanding of Department of Defense requirements and standards is a plus