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Embedded Machine Learning Engineer Jobs in Miami, FL

Opendoor

Machine Learning Engineer

Miami, FL · On-site

About Opendoor At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It ...

Opendoor

Machine Learning Engineer

Miami, FL · On-site

$117K - $154K/yr

About the Role -- Senior and Above You're interviewing for Opendoor's ML team which seeks to automate and refine every decision made in our product. We don't slot into silos; you'll build where you ...

Allvue Systems

Machine Learning Engineer II

Coral Gables, FL · On-site

$92K - $126K/yr

Job Summary The Machine Learning Engineer II supports the discovery, design, and delivery of AI- and automation-enabled solutions that improve operational workflows. The role partners with business ...

YO AI Labs

Machine Learning Engineer - Remote

Miami, FL · Remote

$80 - $120/hr

Remote Job Summary We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software ...

Varsity Tutors

Machine Learning Tutor

Sunrise, FL · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Hialeah, FL · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Showing results 21-40

All JobsEmbedded Machine Learning Engineer JobsEmbedded Machine Learning Engineer Jobs in Miami, FL

Embedded Machine Learning Engineer information

See Miami, FL salary details

$67K

$146.7K

$166.4K

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

As of Sep 15, 2026, the average yearly pay for embedded machine learning engineer in Miami, FL is $146,703.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,800.00 and $165,500.00 per year, depending on experience, location, and employer.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What are popular job titles related to Embedded Machine Learning Engineer jobs in Miami, FL?

For Embedded Machine Learning Engineer jobs in Miami, FL, the most frequently searched job titles are:

What job categories do people searching Embedded Machine Learning Engineer jobs in Miami, FL look for?

The top searched job categories for Embedded Machine Learning Engineer jobs in Miami, FL are:

What cities near Miami, FL are hiring for Embedded Machine Learning Engineer jobs?

Cities near Miami, FL with the most Embedded Machine Learning Engineer job openings:

Embedded Machine Learning Engineer jobs near you

Machine Learning Engineer

Miami, FL • On-site

Opendoor
See more jobs at Opendoorexternal

Full-time

Re-posted 27 days ago

Job description

About Opendoor
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We've built an end-to-end online experience that has already helped thousands of people and we're just getting started.
About the Role - Senior and Above
You're interviewing for Opendoor's ML team which seeks to automate and refine every decision made in our product. We don't slot into silos; you'll build where you have the most impact and the most fun.
These are builder roles across the ML stack. Wherever you land, you'll be doing one of three things:
  • Building models in business-critical contexts like pricing, risk, repairs, and decision optimization. Leverage frontier techniques to extend our capabilities into the unstructured world of real estate.
  • Building the intelligent services that bring structured, precise decision-making into the highly unstructured world of real estate.
  • Building platforms that accelerate how fast our models learn. How fast we learn dictates how fast this company can grow.

You'll work directly with researchers, product, and operations to build the automation that scales in the real world. Our systems must be agile, accurate, and resilient in a heterogeneous space. We are growing fast and this work is at the core.
This isn't a role for everyone. We choose hard mode. We're process-light, high-trust, and we don't put artificial boundaries between you and the work. You'll be expected to understand how your piece connects to the product and communicate at that level. We don't have project managers, we don't have scrum. We do reviews, proposals, demos, and trust.
What We're Looking For
You ship. You pick the boring solution when boring is right and the novel one when it isn't. You know when "good enough and shipped today" beats "perfect next quarter."
You have high agency. You don't wait for permission or a perfectly scoped ticket. You see the problem, take ownership end-to-end, and pull in whoever you need. Lean teams, significant latitude, real accountability.
You run at unclear problems. The most valuable problems here don't come with a playbook - messy data, imperfect ground truth, markets that shift under you. Ambiguity is the job, not an obstacle to it.
You hold a high standard. You measure twice and cut once. You review code, raise the bar on everything around you, and treat the quality of our end-to-end judgment as your problem.
You think in first principles. You have opinions on architecture, distributed systems, ML lifecycle tradeoffs, and the constraints and tripwires of operating models in a high-stakes environment.
You default to AI. You've already integrated modern AI tools into your daily workflow. You use them to move faster, not as a crutch.
You communicate well. You write clear design docs, give useful code reviews, push back on bad ideas without making it personal, and can land a technical tradeoff with a non-technical stakeholder.
You believe in what we're building. Not hype, conviction. You see the opportunity in what we're doing and you want to be part of finishing it.
You have fun. We stay human when times are hard. The task is daunting, but we're all in it together.
What You'll Do
  • Build and train models that real customers and real money depend on - pricing, automation, and decision systems in production
  • Work side-by-side with researchers and analysts to turn prototypes into clean, testable, production-ready code and systems
  • Own model pipelines end-to-end: data ingestion, training, validation, versioning, deployment, and monitoring
  • Design, build, and evolve mission-critical services and APIs that connect to real-world, messy operations
  • Build the platform that accelerates the full ML lifecycle: agentic research, automated retraining, experimentation, deployment, monitoring
  • Proactively tackle real-world challenges like sparsity, data drift, and model decay in a volatile market
  • Use AI tools daily and help push them further than anyone else in the industry
  • Lead technical design reviews, mentor teammates, and raise the bar on everything around you

Qualifications
  • Senior-level or above: deep experience shipping and operating production ML systems, ML-adjacent services, or data/ML platforms
  • Strong fundamentals in Python; comfortable picking up new ones
  • Proficiency with statistics and ability to reason distributionally; has put it to work with real-world monitoring of ML systems
  • Expertise with the end-to-end ML lifecycle (training, evaluation, deployment, monitoring, and iteration) and associated tooling (e.g. MLflow, Airflow, Spark, Delta Lake)
  • Demonstrated ability to make and communicate design decisions and tradeoffs across stakeholders
  • Based in or willing to relocate to Miami, Toronto, or Seattle

Nice to Have
  • ML systems experience in business-critical domains: pricing, forecasting, logistics, marketplaces, risk
  • Streaming and event-driven systems (e.g. Kafka), gRPC, Redis, or workflow engines
  • Interest in real estate or other messy, high-stakes domains with imperfect data

Interview Process
We move fast. Typically:
  • Recruiter phone screen (15 min)
  • A 60 minute technical deep dive to understand a past problem or project you've worked on
  • Two 60 minute pairing-style technical reviews

We're not running these to see if you can finish a problem under pressure. We want to know what it's like to work with you. Before each interview you'll receive an email on what to expect.
Not a perfect fit on paper but clearly excellent? Apply anyway and tell us why in your cover letter. We value T-shaped people. If you have deep expertise in an adjacent area and a strong point of view on how it applies here, that's exactly who we want to talk to.
About Opendoor
At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership, giving people the freedom to buy and sell on their own terms. We've built an end-to-end online experience that has already helped thousands of people - and we're just getting started.

Apply