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Remote Embedded Machine Learning Jobs in Orlando, FL

Worth AI

Data Platform Engineer

Orlando, FL · On-site +1

$106K - $128K/yr

Background supporting machine learning or real-time decisioning use cases from a platform point of ... All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town ...

Worth AI

Data Platform Engineer

Orlando, FL · Remote

$117K - $140K/yr

Background supporting machine learning or real-time decisioning use cases from a platform point of ... All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town ...

Worth AI

Data Platform Engineer

Orlando, FL · On-site +1

$106K - $128K/yr

Background supporting machine learning or real-time decisioning use cases from a platform point of ... All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town ...

Consor Engineers

Proposal Coordinator

Kissimmee, FL · On-site +1

Coordinate with subconsultants and remote team members to compose proposal text with a consistent ... copy machines. May occasionally be exposed to noise. * While performing the duties of this job ...

Consor Engineers

Proposal Coordinator

Kissimmee, FL · On-site +1

Coordinate with subconsultants and remote team members to compose proposal text with a consistent ... copy machines. May occasionally be exposed to noise. * While performing the duties of this job ...

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All JobsEmbedded Machine Learning JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in Orlando, FL

Remote Embedded Machine Learning information

See Orlando, FL salary details

$65.3K

$143.2K

$162.4K

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

As of Aug 9, 2026, the average yearly pay for remote embedded machine learning in Orlando, FL is $143,186.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,800.00 and $161,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a remote embedded machine learning engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by remote embedded machine learning engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are popular job titles related to Remote Embedded Machine Learning jobs in Orlando, FL? For Remote Embedded Machine Learning jobs in Orlando, FL, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in Orlando, FL look for? The top searched job categories for Remote Embedded Machine Learning jobs in Orlando, FL are:
What cities near Orlando, FL are hiring for Remote Embedded Machine Learning jobs? Cities near Orlando, FL with the most Remote Embedded Machine Learning job openings:
Remote Embedded Machine Learning jobs near you

Data Platform Engineer

Worth AI

Orlando, FL • On-site, Remote

$106K - $128K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 10 days ago

Job description

Worth AI, a leader in the computer software industry, is looking for a talented and experienced Data Platform Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.

As a Data Platform Engineer, you will design, build, and operate the core data services that power our products and analytics. You'll own end-to-end data pipelines and API services that ingest, process, and expose high-quality data to internal customers (data science, analytics, product, and other engineering teams) and external partners.

You'll be part of a small, high-impact team that treats the data platform as a product with strong SLAs, and reliable self-service for internal and external users.

Responsibilities

What you'll do:

  • Architect and implement entity resolution logic to de-duplicate and link disparate data points into unified "Golden Records" for businesses and individuals
  • Design and maintain a high-performance global business knowledge graph and ontology to map complex ownership chains, UBOs, and hidden risk relationships across international borders
  • Implement a hybrid storage strategy that bridges graph databases for relationship mapping with document and search stores for rich metadata and adverse media content
  • Optimize the platform for real-time risk assessment, ensuring the ability to traverse multiple levels of ownership in milliseconds to support automated "Go/No-Go" onboarding decisions
  • Design and build scalable data services and APIs for ingesting, transforming, and serving data across the company
  • Develop and maintain batch and streaming data pipelines using modern data processing frameworks and AWS cloud-native tooling
  • Own the reliability, performance, and API first data platform, including monitoring, alerting, and on-call where appropriate
  • Implement best practices for data modeling, quality, lineage, and governance to ensure trustworthy, well-documented datasets
  • Work closely with data scientists, analysts, and application engineers to understand their needs and translate them into robust platform capabilities
  • Drive automation and standardization through CI/CD, model as a service, and reproducible environments
  • Help define and evolve the architecture of our data platform as a true internal service with clear contracts, SLAs, and versioned APIs

Requirements

    • Expertise in Graph Ecosystems: Hands-on experience with Graph databases (e.g., Neo4j, AWS Neptune, or TigerGraph) and query languages like Cypher or Gremlin
    • Identity & Linkage Mastery: Proven experience with Entity Resolution or Record Linkage (e.g., using tools like Senzing, Quantexa, or custom probabilistic matching models)
    • Schema Design: Ability to design flexible ontologies that handle evolving regulatory data (e.g., changing PEP definitions or Sanction list formats)
    • API Performance for Graphs: Experience building GraphQL or REST APIs specifically optimized for graph traversals and deep-tree lookups
    • Experience building centralized data platforms or "data-as-a-service" offerings at scale (e.g., at a large tech or cloud-native company)
    • Strong software engineering skills in at least one language commonly used for data and services (e.g., Python, Java, Go, Rust)
    • Hands-on experience building data pipelines and ETL/ELT workflows on a major cloud provider (AWS preferred)
    • Experience with modern data stack tools such as Spark/Flink, Kafka/Kinesis, Airflow/managed schedulers, and data warehouses (e.g., Snowflake, Redshift, BigQuery, Databricks)
    • Familiarity with DevOps practices: CI/CD, containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform)
    • Strong focus on observability (metrics, logs, traces), resilience, and building early warning signals
    • Comfort collaborating cross-functionally and communicating clearly with both technical and non-technical stakeholders.

Nice to Have

    • Background supporting machine learning or real-time decisioning use cases from a platform point of view
    • Compliance Domain Knowledge: Understanding of AML, CTF, and KYC/KYB data structures (e.g., LEIs, ISO 20022)
    • Geospatial Data: Experience handling global address normalization and geospatial indexing for risk detection

** All Remote Hires - will be required to travel to Orlando, Florida at least twice per year for Town Halls and team collaboration in addition to orientation in Orlando, Florida

Benefits

    • Health Care Plan (Medical, Dental & Vision)
    • Retirement Plan (401k, IRA)
    • Life Insurance
    • Flexible Paid Time Off
    • 9 paid Holidays
    • Family Leave
    • Work From Home
    • Free Food & Snacks (Orlando)
    • Wellness Resources

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