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Embedded Machine Learning Jobs in Florida (NOW HIRING)

Apple

GPU Design Verification Engineer

Orlando, FL · On-site

$127K - $155K/yr

... embedded graphics cores. You will also collaborate with members of other disciplines and top ... Familiarity with machine learning and AI processing in GPU architectures. Experience with Formal ...

Apple

GPU Design Verification Engineer

Orlando, FL

$127K - $155K/yr

... embedded graphics cores. You will also collaborate with members of other disciplines and top ... Familiarity with machine learning and AI processing in GPU architectures. Experience with Formal ...

Crowe LLP

Senior AI Engineer

Tampa, FL · On-site +1

$98K - $135K/yr

... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

Crowe LLP

Senior AI Engineer

Miami, FL · On-site +1

$99K - $137K/yr

... innovation, embedded AI capabilities, and global delivery resources-all in service of solving ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

TECO Peoples Gas

Manager Analytics & AI

Tampa, FL · On-site

... are embedded into operational workflows and drive intended business outcomes. • Applies ... g., machine learning, optimization, decision automation, or AI‑assisted analytics) in real ...

University of Miami

Post Doctoral Associate

Coral Gables, FL · On-site

$46K - $63K/yr

... machine learning. * Design and conduct experimental studies involving robotic platforms such as ... Experience: * Extensive experience in robotics system design, real-time control, and embedded ...

Raytheon

Software Engineer II

Orlando, FL

$91K - $124K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with hardware-software integration and embedded system testing. * Active and ...

Raytheon

Software Engineer II

Miami, FL

$93K - $127K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with hardware-software integration and embedded system testing. * Active and ...

Raytheon

Software Engineer II

Miami, FL · On-site

$93K - $127K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with hardware-software integration and embedded system testing. * Ability to obtain ...

Raytheon

Software Engineer II

Orlando, FL

$91K - $124K/yr

... time systems, machine learning, cybersecurity, and DevOps. Join our team of creative problem ... Experience with hardware-software integration and embedded system testing. * Ability to obtain ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Florida

Embedded Machine Learning information

See Florida salary details

$52.3K

$114.6K

$130K

How much do embedded machine learning jobs pay per year?

As of Jun 25, 2026, the average yearly pay for embedded machine learning in Florida is $114,622.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $129,300.00 per year, depending on experience, location, and employer.

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

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 Florida? The most popular types of Embedded Machine Learning jobs in Florida are:
What are popular job titles related to Embedded Machine Learning jobs in Florida? For Embedded Machine Learning jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Florida look for? The top searched job categories for Embedded Machine Learning jobs in Florida are:
Embedded Machine Learning jobs near you

AI and Agentic AI Risk Management Senior Specialist

Nubank

Miami, FL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 20 days ago

Job description

About Us
Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.
Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.
Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company's Most Innovative Companies, and Forbes World's Best Bank. Visit our institutional page https://international.nubank.com.br/careers/
About the team
At Nubank we heavily rely on Data, Machine Learning, and increasingly on Generative and Agentic AI to drive our strategy and deliver the best experience and products to our customers. The Model Risk team plays a crucial role in ensuring the risks associated with our models and AI systems are understood and under control. We are now building a dedicated AI Risk Management capability to address the emerging risks of advanced AI - including LLM-powered and autonomous agentic systems - with a focus on AI quality, model and agent behavior, and the platform controls that keep these systems safe and reliable across internal and customer-facing use cases.
About the role
This is a senior, hands-on technical position. You will help define what model risk management looks like for AI and Agentic AI at Nubank - building and enhancing the frameworks, not just inheriting them. You will perform independent assessments of AI systems for quality, behavior, and robustness, and help design the guardrails and platform-level controls that govern their safe use. You'll act as a credible technical peer to first-line engineering and AI development teams, providing practical guidance on AI risk without slowing responsible innovation. This role focuses on AI quality, agentic behavior, and platform controls; cybersecurity, data privacy, and fraud-specific matters sit with partner functions and are out of scope.
What you will do
AI Risk Framework & Governance
  • Build and continuously enhance the risk management framework for AI and Agentic AI systems, including inventory standards, assessment methodologies, control design, and issue management.
  • Inventory and map Nubank's AI use cases to surface gaps, materiality, and the most critical risks, and define prioritized mitigation actions.
  • Assess whether first-line monitoring is effective, proportionate to model risk, and sufficient to keep AI systems fit for purpose over time.

Independent AI Assessment
  • Perform independent technical assessments across generative AI, and agentic workflows, covering data, assumptions, methodology, testing, behavior, and monitoring.
  • Assess risks in LLM-powered applications, including RAG pipelines, tool use, autonomy boundaries, model/agent quality, human oversight, and hallucination risk.
  • Identify and document model limitations, failure modes, and emerging AI risks, including drift, instability, fairness, and robustness concerns.

Controls, Platform & Enablement
  • Influence first-line teams on platform architecture and embedded controls for the safe deployment and monitoring of AI.
  • Build Key Risk Indicators (KRIs) and metrics for continuous monitoring of AI risk.
  • Develop tools, evals, analyses, and playbooks (including AI-enabled automation) to improve the speed, scale, and effectiveness of AI governance and validation.

Advisory & Advocacy
  • Serve as a trusted advisor across the AI/ML lifecycle, evaluating new use cases for materiality and governance requirements prior to deployment.
  • Discuss and report AI risk status and independent opinions to stakeholders, including senior managers and, where relevant, regulators.
  • Champion AI risk management as a strategic enabler of safe and scalable AI adoption, and build AI risk literacy across engineering, product, and risk teams.
  • Work in a multicultural, diverse, and highly skilled environment.

Requirements we are looking for
  • Education: A bachelor's or master's degree in a quantitative field (computer science, data science, statistics, mathematics, engineering, or related).
  • Hands-on AI/ML experience: A track record developing or validating AI/ML models and systems, ideally a candidate who has moved from an AI / Machine Learning Engineer background into model risk, governance, or risk management. You don't need to have trained foundation models from scratch, but you need solid, current technical depth.
  • Strong technical foundations: Proficiency in Python, SQL, and modern ML tooling; familiarity with LLMs, RAG systems, prompt engineering, and AI agent frameworks.
  • Evaluation and testing: Experience evaluating and testing ML and generative AI systems, including custom evals, benchmarking, stress testing, and drift/degradation monitoring.
  • Risk management experience: Demonstrated experience in risk identification, control definition, and framework building; understanding of model risk governance principles and independent effective challenge.
  • Data skills: Experience working with large datasets and building dashboards and analyses to support risk visibility.
  • High agency and adaptability: Comfortable operating in ambiguity, synthesizing fragmented technical and business context into a clear view of how complex AI systems actually work, and making sound judgments without a complete playbook.
  • Influencing skills: Able to engage and align stakeholders across first and second lines of defense as a credible technical peer.
  • Communication: Strong written and verbal skills, you can explain AI risk to a data scientist and to a regulator, and use different language for each.
  • Advanced or fluent English: You will meet with partners and stakeholders across countries and prepare documentation and presentations in English.
  • PLUS: Experience in a 2nd or 3rd line of defense.
  • PLUS: Familiarity with regulatory Model Risk Management and AI frameworks (e.g., SR 11-7 / SR 26-2 / OCC 2011-12, NIST AI RMF, EU AI Act).

Total compensation includes base salary, RSUs and benefits. Base salary range: US$108k - US$131k.
Benefits
  • Opportunity of earning equity at Nu
  • Medical Insurance
  • Dental and Vision Insurance
  • Life Insurance and AD&D
  • Extended maternity and paternity leaves
  • Nucleo - Our learning platform of courses
  • NuLanguage - Our language learning program
  • NuCare - Our mental health and wellness assistance program
  • Extended maternity and paternity leaves
  • 401K
  • Saving Plans - Health Saving Account and Flexible Spending Account
  • Work-from-home Allowance
  • Relocation Assistance Package, if applicable.
Work Model for this Role
Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration.
For more details, visit https://building.nubank.com/nu-hybrid-work-model/

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