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Embedded Machine Learning Engineer Jobs in Clearwater, FL

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Bigdata Engineer

Tampa, FL

$52.75 - $69.75/hr

Job Title: Bigdata Engineer Location: Tampa, FL Duration: 12+ Months Contract to hire Job ... Deploy the machine learning model and serve its outputs as RESTful API calls. Understand the ...

Bigdata Engineer

Tampa, FL · On-site

$52.75 - $69.75/hr

... machine learning/Big Data • applications using open source tools such as Scala, Java, Python ... Interface with Engineering/Operations/System Admin/Data Scientist teams to ensure data • ...

... design, machine learning, and embedded systems to enhance autonomy in challenging conditions ... Work closely with senior engineers on research and prototyping efforts. * Perform other duties as ...

They are seeking an ML Ops Engineer to design, build, and maintain the infrastructure and pipelines for Machine Learning model training and deployment, collaborating with a cross-functional data team.

Be Seen First

Deploy and optimize algorithms on embedded systems (Jetson, GPU-enabled platforms) with focus on ... Familiarity with computer vision and machine learning tools such as OpenCV, PyTorch, or TensorFlow

Principal Software Engineer

Tampa, FL

$127K - $171K/yr

Yourexpertisein both machine learning and operations will be essential in creating efficient and reliable ML pipelines.A background in data engineering, including experience with data pipelines and ...

Principal Software Engineer

Tampa, FL · On-site

$127K - $171K/yr

Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. A background in data engineering, including experience with data pipelines ...

... design, machine learning, and embedded systems to enhance autonomy in challenging conditions ... Work closely with senior engineers on research and prototyping efforts. * Perform other duties as ...

... design, machine learning, and embedded systems to enhance autonomy in challenging conditions ... Work closely with senior engineers on research and prototyping efforts. * Perform other duties as ...

Develops and maintains solutions in machine learning, reporting, visualization, predictive modeling ... Bachelor's degree in information systems, data science, computer/electrical engineering, or related ...

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 ...

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Design, develop, and deploy enterprise AI solutions spanning traditional machine learning ... Mentor junior AI engineers and elevate the broader organization's AI engineering capabilities

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Showing results 1-20

Embedded Machine Learning Engineer information

See Clearwater, FL salary details

$64.5K

$141.4K

$160.4K

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

As of Jul 18, 2026, the average yearly pay for embedded machine learning engineer in Clearwater, FL is $141,370.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,200.00 and $159,400.00 per year, depending on experience, location, and employer.

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

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 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 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 Clearwater, FL? For Embedded Machine Learning Engineer jobs in Clearwater, FL, the most frequently searched job titles are:
Infographic showing various Embedded Machine Learning Engineer job openings in Clearwater, FL as of July 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $141,370 per year, or $68 per hour.
Senior AI Engineer - SFL Scientific

Senior AI Engineer - SFL Scientific

Deloitte

Tampa, FL

$98K - $135K/yr

Other

Re-posted 28 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 90 frontline employees who took The Breakroom Quiz

59th of 148 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
  • AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
  • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices...

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