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Internship Audio Machine Learning Jobs in Washington

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

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All JobsAudio Machine Learning JobsInternship Audio Machine Learning JobsInternship Audio Machine Learning Jobs in Washington

Internship Audio Machine Learning information

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

AspectInternship Audio Machine LearningAudio Signal Processing Intern
Required SkillsMachine learning, programming, audio analysisSignal processing, audio engineering, MATLAB
Work EnvironmentResearch labs, tech companies, AI-focused teamsAudio labs, audio equipment companies, research institutions
Industry UsageAI, speech recognition, music analysisAudio engineering, sound design, acoustics

Internship Audio Machine Learning focuses on developing algorithms for audio data, emphasizing machine learning techniques. In contrast, Audio Signal Processing Interns work on analyzing and manipulating audio signals using signal processing methods. Both roles often require programming skills and are found in tech and audio industries, but their core focus differs: AI-driven analysis versus traditional signal processing.

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:
Internship Audio Machine Learning jobs near you

Lead Machine Learning Engineer

Hirekeyz Inc

Fort Belvoir, VA • On-site

$115K - $152K/yr

Contractor

Re-posted 26 days ago

Job description

Role: Lead Machine Learning Engineer

Location: Ft. Belvoir, VA (On-site with Hybrid Option)

Duration: Long Term Contract

Job Description:

As a consultant, will be working to assist a DoD U.S. Army Command to create cybersecurity solutions working with cloud-based architecture (AWS Services).  You will work directly the stakeholders to understand requirements and work with Army’s Security teams to ensure the technologies available to the Government can be turned into solutions that they can use. Liaise with government software vendors and other asset creators; lead coordination of point solutions into broader capabilities for Army Defense Cyber Operations (DCO).  You will be helping our military defend our cyber security infrastructure by delivering software capabilities. 

Required Skills:

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field
  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
  • At least 8 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
  • Proven track record in designing, building, and/or delivering ML models and components that solve real-world business problems, while working in collaboration with other technical teams.
  • Collaborate as part of a cross-functional Agile team to create and enhance capabilities that enables state-of-the-art big data and ML applications.
  • Retrain, maintain, and monitor models in production.
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.
  • Be a trusted advisor to the Government to ensure all third party vendors platforms and code delivered is “fit for purpose”
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and
  • Use programming languages like Python, Scala, or Java.
  • Abilty to mentor and coach junior resources with delivery tasks.
  • Self-motivated, with the ability to work effectively both independently and in a team environment

Preferred Skills:

  • Certifications in Machine Learning / Artificial Intelligence / Data Science
  • Familiarity with agile development methodologies
  • 5-8 years of experience in a ML/AI development and/or lead role