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Embedded Machine Learning Jobs in Connecticut (NOW HIRING)

Our clients are IT and business leaders worldwide, relying on the platform embedded in their ... What You Will Need * 8-12 years of experience in data science, machine learning, or AI, with at ...

... embedded into systems and workflows, preventing bad data at the source rather than correcting it ... Generative AI, machine learning, and advanced analytics * Enterprise data and analytics platforms

Our clients are IT and business leaders worldwide, relying on the platform embedded in their ... What You Will Need * 8-12 years of experience in data science, machine learning, or AI, with at ...

Our clients are IT and business leaders worldwide, relying on the platform embedded in their ... What You Will Need * 8-12 years of experience in data science, machine learning, or AI, with at ...

Power Electronics Engineer

Groton, CT ยท On-site

$111K - $131K/yr

... embedded processors is required. Previous experience laying out boards and/or managing layout ... opportunities and learning experiences. You will work in a small company environment where ...

Power Electronics Engineer

Groton, CT ยท On-site

$111K - $131K/yr

... embedded processors is required. Previous experience laying out boards and/or managing layout ... opportunities and learning experiences. You will work in a small company environment where ...

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Embedded Machine Learning information

See Connecticut salary details

$66.6K

$145.9K

$165.5K

How much do embedded machine learning jobs pay per year?

As of Jun 7, 2026, the average yearly pay for embedded machine learning in Connecticut is $145,912.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,100.00 and $164,600.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in embedded machine learning roles?

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

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

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are the most commonly searched types of Embedded Machine Learning jobs in Connecticut? The most popular types of Embedded Machine Learning jobs in Connecticut are:
Infographic showing various Embedded Machine Learning job openings in Connecticut as of May 2026, with employment types broken down into 1% Locum Tenens, 4% Internship, 62% Full Time, 31% Part Time, 1% Temporary, and 1% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $145,912 per year, or $70.2 per hour.

Vice President, Research and Development

CooperCompanies

Trumbull, CT โ€ข On-site

Full-time

Medical, Retirement, PTO

Posted 17 hours ago


Job description

Job Description
The Vice President of Research & Development (VP, R&D) is a senior executive responsible for defining and executing the company's innovation strategy to deliver safe, effective, and commercially successful medical devices. This leader will oversee the full product lifecycle-from concept and feasibility through development, verification/validation, regulatory submission, and post-market support-while ensuring alignment with business objectives, regulatory requirements, and patient needs.
The Vice President leads a Research and Development organization of 75 team members and partners closely with Regulatory, Quality, Clinical, Operations, and Commercial leaders to accelerate time-to-market, build scalable development capabilities, and foster a culture of scientific excellence, accountability, and innovation.
Responsibilities
Essential Functions & Accountabilities:
R&D & Technology Strategy:
  • Define and execute a long-term R&D strategy that integrates medical hardware, embedded software, cloud platforms, data analytics, and AI/ML capabilities.
  • Build and manage a balanced portfolio spanning incremental innovation, platform development, and disruptive technologies.
  • Align R&D priorities with corporate strategy, multi-year financial plans, and public company growth commitments.

Software & AI-Enabled Product Development:
  • Lead development of software-as-a-medical-device (SaMD), software in a medical device (SiMD), digital health platforms, and AI/ML algorithms.
  • Establish development practices compliant with IEC 62304, FDA SaMD guidance, Good Machine Learning Practices (GMLP), and cybersecurity standards.
  • Ensure AI systems are clinically validated, explainable, secure, and ethically deployed, with strong post-market monitoring and model lifecycle management.

Regulatory, Quality & Compliance Leadership:
  • Ensure R&D outputs meet global regulatory requirements including FDA, EU MDR/IVDR, and international software and AI regulations.
  • Partner with Regulatory and Quality to support major submissions, inspections, and responses to regulatory inquiries.
  • Embed quality-by-design, software risk management, data integrity, and cybersecurity throughout development.

Clinical & Evidence Strategy:
  • Collaborate with Clinical Affairs to generate clinical evidence supporting software, algorithms, and connected device claims.
  • Support real-world evidence (RWE) and data-driven performance monitoring post-launch.
  • Integrate human factors, usability engineering, and patient experience into product design.

Public Company Governance & Executive Accountability:
  • Provide clear, data-driven updates on R&D performance, risks, and milestones to executive leadership and the Board of Directors.
  • Support investor confidence through predictable execution, portfolio clarity, and credible long-range innovation plans.
  • Partner with Finance and Legal to support earnings forecasts, disclosures, and risk management related to R&D initiatives.

Leadership & Organization Development:
  • Build and lead world-class, multidisciplinary teams spanning hardware, software, data science, systems engineering, and clinical.
  • Attract, retain, and develop top technical and leadership talent in competitive global markets.
  • Foster a culture of accountability, innovation, and continuous improvement.

Operational Excellence & Scalability:
  • Implement modern development tooling, agile practices (where appropriate), and portfolio governance to improve speed and predictability.
  • Optimize R&D spending, vendor strategy, and global development footprint.
  • Ensure design for manufacturability, scalability, and lifecycle cost efficiency.

Travel:
  • Able to travel 25% + (60+ days) nationally and internationally.

Qualifications
Knowledge, Skills and Abilities:
Required:
  • PhD, MS, or equivalent advanced degree in Engineering, Computer Science, Biomedical Engineering, or related field.
  • 15+ years of progressive R&D leadership experience in medical devices, digital health, or regulated healthcare technology.
  • Proven track record delivering software- and AI-enabled medical products from concept to global commercialization.
  • Deep knowledge of medical device regulations, software standards, and AI governance in regulated environments.
  • Extensive experience operating within public company governance and compliance frameworks.

Preferred:
  • Prior P&L or portfolio leadership responsibility.
  • Experience with cloud-based platforms, data pipelines, cybersecurity, and AI lifecycle management.
  • Exposure to M&A technical due diligence and post-acquisition integration.
  • Global leadership experience across North America, Europe, and Asia.

Leadership Competencies:
  • Strategic & Systems Thinker: Integrates hardware, software, data, and AI into cohesive platforms.
  • Execution-Driven: Delivers predictable outcomes in fast-moving, highly regulated environments.
  • Technically Credible: Respected by engineers, clinicians, regulators, and executive peers.
  • Board-Ready Communicator: Engages effectively with executive leadership and Directors.
  • Patient-First Mindset: Anchors innovation in safety, usability, and clinical outcomes.

As an employee of CooperSurgical, you'll receive an outstanding total compensation plan. As we believe your compensation goes beyond your paycheck, we offer a great compensation package, medical coverage, 401(k), parental leave, fertility benefits, paid time off for vacation, personal, sick and holidays, and multiple other perks and benefits. Please visit us at www.coopersurgical.com to learn more about CooperSurgical and the benefits of becoming a member of our team.
To all agencies: Please, no phone calls or emails to any employee of CooperSurgical about this opening. All resumes submitted by search firms/employment agencies to any employee at CooperSurgical via-email, the internet or in any form and/or method will be deemed the sole property of CooperSurgical, unless such search firms/employment agencies were engaged by CooperSurgical for this position and a valid agreement with CooperSurgical is in place. In the event a candidate who was submitted outside of the CooperSurgical agency engagement process is hired, no fee or payment of any kind will be paid.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. If you are interested in applying and require special assistance or accommodations due to a disability, please contact us at talent.acquisition@coopersurgical.com.