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Embedded Machine Learning Jobs in Florida (NOW HIRING)

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Senior Wireless Firmware Engineer

Tampa, FL · Remote

$112K - $149K/yr

Our SaaS platform uses WiFi, advanced AI, and machine learning to create the future of connected ... You will work across embedded firmware, wireless drivers, and system-level software to enable high ...

Total Quality Logistics

AI Architect

Tampa, FL · On-site

... deeply embedded into business workflows. You will partner closely with Engineering, Product ... Hands-on experience with Azure OpenAI, Azure Machine Learning, Azure AI Search, Microsoft Fabric ...

TQL

AI Architect

Tampa, FL

$59.50 - $78.50/hr

... deeply embedded into business workflows.You will partner closely with Engineering, Product ... Hands-on experience with Azure OpenAI, Azure Machine Learning, Azure AI Search, Microsoft Fabric ...

Knorr-Bremse

Senior Software Engineer

Melbourne, FL · On-site

$113K - $149K/yr

Experience with real-time and embedded development, FPGA experience, board bring-up, peripheral ... Exposure to AI frameworks or machine learning libraries. * Demonstrated experience in developing ...

Brooksource

Full Stack Developer - Robotics

Orlando, FL · On-site

$130K/yr

Familiarity with real-time systems, embedded development, or control systems. * Strong ... Exposure to machine learning, computer vision or control theory in robotics contexts. * Passion for ...

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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
Vice President, AI Applied Engineering

Vice President, AI Applied Engineering

InspereX

Delray Beach, FL • On-site

$169K - $217K/yr

Full-time

Posted 7 hours ago

Job description

Description:OverviewInspereX is seeking a highly capable and hands-on AI Applied Engineering leader to design,build, and embed AI capabilities directly into our core platforms, workflows, and client-facingapplications.This role will focus on translating data, analytics, and AI capabilities into practical, productiongradesolutions that enhance trading, distribution, advisor engagement, and client experienceacross platforms such as BondNav and InCapNet.Working closely with Engineering, Product, and Business leadership, this individual will play acritical role in advancing AI across the firm, moving from experimentation to real-worldapplication and measurable business impact.
Key Responsibilities• Design and implement AI and machine learning solutions directly within business workflows,trading processes, and client-facing applications• Embed AI capabilities into core platforms such as BondNav and InCapNet, including pricingsupport, trade workflows, recommendation engines, and advisor tools• Develop and deploy models supporting use cases such as:? pricing optimization and execution support? next-best-action for sales and distribution? advisor and client intelligence? portfolio optimization, risk analytics, and decision support? workflow automation and intelligent process enhancement• Work directly with business leaders and front-line associates to identify opportunities toleverage data, analytics, and AI within day-to-day workflows and decision-making• Partner with Product and Engineering teams to integrate AI into application architecture, APIs,and user experiences• Work closely with Data, AI, and Digital Enablement leadership to align AI initiatives withbroader enterprise data strategy and business priorities• Build scalable, production-grade AI systems with a focus on performance, reliability, and realtimedecisioning• Rapidly prototype and iterate on AI use cases, moving from concept to production efficiently• Ensure AI solutions are intuitive, explainable, and aligned to end-user workflows• Contribute to the development of a modern AI engineering capability across the firmRequirements:

Required Experience

• Strong hands-on experience in AI/ML engineering, data science, and advanced analytics

• Proven experience building and deploying AI/ML solutions in production environments

• Strong foundation in data analysis, statistical modeling, and translating data into actionable

insights

• Experience working directly with business stakeholders to define and implement data-driven

and AI-enabled solutions

• Experience working with financial data and/or capital markets workflows (fixed income,

trading, portfolio analytics preferred)

• Proficiency in Python and modern ML frameworks (TensorFlow, PyTorch, or equivalent)

• Experience with data platforms such as Databricks, Snowflake, or similar

• Experience integrating AI into applications via APIs, microservices, and event-driven

architecture

• Familiarity with real-time data processing and decisioning systems


Preferred Qualifications

• Experience with fixed income, structured products, or trading environments

• Exposure to pricing models, execution workflows, or market data systems

• Experience with portfolio optimization, risk modeling, and advanced analytics use cases

• Experience with GenAI, LLMs, and agent-based systems

• Experience building recommendation systems or decision-support tools

• Understanding of data governance and model lifecycle management


What Success Looks Like

• AI capabilities are embedded directly into BondNav, InCapNet, and related platforms

• Measurable improvements in trading workflows, sales effectiveness, and advisor engagement

• Increased automation and intelligence within core business processes

• Strong collaboration with business leaders and front-line teams to drive adoption of AI

capabilities

• Faster time-to-market for AI-enabled features and capabilities


Why This Role Matters

This role represents a key step in advancing InspereX’s AI strategy, moving beyond

experimentation to directly integrating AI into the firm’s core platforms, workflows, and

decision-making processes.

The successful candidate will help shape how data, analytics, and AI drive real business impact

across trading, distribution, risk, and client engagement.

Apply