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Embedded Machine Learning Internship Jobs in Ithaca, NY

... Initiative and is embedded within the interdisciplinary cluster "Advancing Health through ... Conduct high-quality, externally visible research in applied mathematics, machine learning, and ...

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Embedded Engineering: Design complete embedded systems, including schematic capture, custom PCB ... AI & Tools: Knowledge of computer vision frameworks (OpenCV), machine learning libraries, or ...

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Embedded Engineering: Design complete embedded systems, including schematic capture, custom PCB ... AI & Tools: Knowledge of computer vision frameworks (OpenCV), machine learning libraries, or ...

Embedded Machine Learning Internship information

See Ithaca, NY salary details

$24.6K

$41.1K

$84.9K

How much do embedded machine learning internship jobs pay per year?

As of Jul 27, 2026, the average yearly pay for embedded machine learning internship in Ithaca, NY is $41,067.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,300.00 and $44,400.00 per year, depending on experience, location, and employer.

What is an Embedded Machine Learning Internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an Embedded Machine Learning Internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.
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What job categories do people searching Embedded Machine Learning Internship jobs in Ithaca, NY look for? The top searched job categories for Embedded Machine Learning Internship jobs in Ithaca, NY are:
What cities near Ithaca, NY are hiring for Embedded Machine Learning Internship jobs? Cities near Ithaca, NY with the most Embedded Machine Learning Internship job openings:
Infographic showing various Embedded Machine Learning Internship job openings in Ithaca, NY as of July 2026, with employment types broken down into 90% Full Time, 8% Part Time, and 2% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $41,067 per year, or $19.7 per hour.
Assistant Professor

Assistant Professor

Howard

Locke, NY • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago


Job description

The Talent Acquisition department hires qualified candidates to fill positions which contribute to the overall strategic success of Howard University. Hiring staff "for fit" makes significant contributions to Howard University's overall mission.

At Howard University, we prioritize well-being and professional growth.

Here is what we offer:

  • Health & Wellness: Comprehensive medical, dental, and vision insurance, plus mental health support
  • Work-Life Balance: PTO, paid holidays, flexible work arrangements
  • Financial Wellness: Competitive salary, 403(b) with company match
  • Professional Development: Ongoing training, tuition reimbursement, and career advancement paths
  • Additional Perks: Wellness programs, commuter benefits, and a vibrant company culture

Join Howard University and thrive with us!

https://hr.howard.edu/benefits-wellness

The Department of Mathematics in the College of Arts and Sciences at Howard University invites applications for a full-time, tenure-track Assistant or Associate Professor position. The department seeks candidates with research expertise and teaching interests in mathematics enhanced artificial intelligence (AI), with applications to radiology, endocrinology, and related biomedical domains. The anticipated start date is August 2026.
This position is part of the Provost's Artificial Intelligence Cluster Hire Initiative and is embedded within the interdisciplinary cluster "Advancing Health through Mathematics-Enhanced AI for Radiology and Endocrinology", jointly led by the College of Arts and Sciences and the College of Medicine. The cluster aims to strengthen university-wide research capacity by recruiting faculty whose scholarship advances mathematical foundations, modeling, and computational methodologies that support AI-driven biomedical discovery, while fostering
collaboration across disciplines.


SUPERVISORY AUTHORITY: The successful candidate is expected to demonstrate a strong commitment to excellence in teaching, mentoring, and service. The faculty member will contribute to the growth of the Department of Mathematics' research and academic programs in data science, applied mathematics, and AI, and will actively participate in interdisciplinary initiatives across the university.


NATURE AND SCOPE:
From a mathematics-centered perspective, this position emphasizes the development and application of mathematical theory, statistical modeling, and computational methods that underpin modern AI and machine learning approaches in biomedical sciences. The cluster seeks to advance quantitative frameworks for imaging, inference, prediction, and decision-making in complex biological and clinical systems. The successful candidate will contribute to an interdisciplinary academic environment through research, teaching, mentorship, and collaboration. Responsibilities include leading independent and collaborative research programs at the interface of mathematics, AI, and biomedical
imaging; contributing to undergraduate and graduate curriculum development; mentoring students; and conducting research that addresses health disparities and promotes inclusive excellence.

PRINCIPAL ACCOUNTABILITIES:
Conduct high-quality, externally visible research in applied mathematics, machine learning, and artificial intelligence, with relevance to biology and medicine.
Develop and sustain an externally funded research program, including collaborative interdisciplinary projects.
Teach undergraduate and graduate courses in mathematics, data science, machine learning, and artificial intelligence.
Supervise and mentor undergraduate and graduate students, postdoctoral scholars, and junior researchers.
Collaborate with faculty across mathematics, medicine, and related disciplines to advance AI-enabled quantitative methods for biomedical applications.

CORE COMPETENCIES:
The Department of Mathematics particularly encourages applicants with expertise in one or more of the following areas:
Mathematical Foundations of AI and Machine Learning:
Optimization, statistical learning theory, inverse problems, uncertainty quantification, dynamical systems, or computational mathematics relevant to AI.
AI and Data-Driven Modeling in Biomedicine:
Development of mathematical and computational methods for imaging, neuroscience, endocrinology, diabetes, or other data-intensive biomedical domains.
Interdisciplinary Research and Collaboration:
Demonstrated ability to collaborate with clinicians, biologists, or engineers to develop mathematically grounded AI/ML approaches for complex biological and medical datasets.

MINIMUM REQUIREMENTS:
Ph.D. in Mathematics, Applied Mathematics, Computer Science, Data Science, Artificial Intelligence, or a closely related field.
Strong research record in mathematics-driven AI or ML, with applications to biology or medicine, evidenced by peer-reviewed publications.
Demonstrated ability or clear potential to secure external research funding.
Evidence of excellence or strong potential in undergraduate and graduate teaching.
Commitment to interdisciplinary collaboration, student mentorship, and advancing diversity, equity, and inclusion in teaching and research.

Compliance Salary Range Disclosure

Compensation Range: $135,000 - $150,000