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Remote Machine Learning Jobs in Orlando, FL (NOW HIRING)

Axiom Bank

Senior Software & AI Engineer

Maitland, FL · On-site +1

$113K - $150K/yr

Prior involvement in greenfield projects where youve contributed to foundational technology decisions Working Conditions This position may be hybrid or fully remote. Occasional evening or weekend ...

Axiom Bank, N.A.

Senior Software & AI Engineer

Maitland, FL · On-site +1

$114K - $150K/yr

Prior involvement in greenfield projects where you've contributed to foundational technology decisions Working Conditions This position may be hybrid or fully remote. Occasional evening or weekend ...

Paynuity

Software Developer

Orlando, FL · Remote

You will start out learning our systems from the ground up, helping to develop secure applications and refactoring existing .NET 2/4 web forms. You will be working in a continuous lifecycle ...

Paynuity

Software Developer

Orlando, FL · Remote

You will start out learning our systems from the ground up, helping to develop secure applications and refactoring existing .NET 2/4 web forms. You will be working in a continuous lifecycle ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Orlando, FL

Remote Machine Learning information

See Orlando, FL salary details

$23.8K

$39.8K

$82.1K

How much do remote machine learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote machine learning in Orlando, FL is $39,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Orlando, FL? The most popular types of Machine Learning jobs in Orlando, FL are:
What are popular job titles related to Remote Machine Learning jobs in Orlando, FL? For Remote Machine Learning jobs in Orlando, FL, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Orlando, FL look for? The top searched job categories for Remote Machine Learning jobs in Orlando, FL are:
What cities near Orlando, FL are hiring for Remote Machine Learning jobs? Cities near Orlando, FL with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Orlando, FL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $39,752 per year, or $19.1 per hour.

Senior Software Engineer, AI Platform

Fortress Information Security

Orlando, FL • On-site, Remote

$140K - $223K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago

Job description

Senior Software Engineer - AI Platform
Location: Remote
Salary Range: $140,541- $223,212, per year, depending on experience and qualifications.
Employment Type: Full-time
Fortress Information Security does not provide employment-based visa sponsorship, now or in the future, for this position.

What you can expect as a Senior Software Engineer - AI Platform at Fortress:
Fortress Information Security is seeking a Senior Software Engineer, AI Platform to help build the foundational AI platform powering intelligent workflows across Fortress products and services. This role focuses on designing and operating the orchestration, retrieval, execution, and platform infrastructure required to support scalable, secure, and reliable AI systems in highly regulated environments.
The ideal candidate brings strong distributed systems and backend engineering experience combined with hands-on experience building production-grade AI infrastructure, orchestration systems, or retrieval platforms. This individual will work across platform, infrastructure, and application layers to help establish the technical foundation for Fortress’s AI strategy.
This role is well-suited for engineers who enjoy solving complex systems problems involving long-running stateful workflows, multi-store retrieval architectures, event-driven systems, observability, and secure multi-tenant infrastructure. Please note: This role is built for a true, current senior engineer. Someone who hits the ground running, drives decisions independently, and raises the bar for the team from day one.


Responsibilities Include:
  • Design, build, and operate orchestration frameworks supporting long-running, stateful AI workflows and agent execution systems
  • Develop distributed retrieval architectures spanning vector, graph, search, and relational data platforms
  • Build shared platform services, reusable runtime components, and tool registries supporting AI capabilities across Fortress products
  • Implement resilient event-driven and change-data-capture (CDC) pipelines with strong consistency, retry, and fault-tolerance guarantees
  • Develop typed APIs and integration contracts supporting AI workflows and platform interoperability
  • Improve scalability, performance, reliability, and operational efficiency across orchestration and retrieval infrastructure
  • Support secure multi-tenant deployments across cloud, hybrid-cloud, and air-gapped environments
  • Build and maintain observability, telemetry, tracing, centralized logging, governance, and policy enforcement tooling
  • Contribute to engineering standards and architectural patterns for orchestration, retrieval, and platform infrastructure
  • Collaborate cross-functionally with platform engineering, product engineering, security, and AI teams to support platform adoption and operational excellence
  • Participate in troubleshooting, incident response, root cause analysis, and operational support activities related to platform infrastructure
  • Continuously evaluate emerging technologies, tooling, and engineering practices relevant to AI infrastructure and distributed systems
Minimum Qualifications:
  • 6+ years of experience in backend, platform, or infrastructure engineering building production distributed systems
  • Strong Python development experience including asynchronous systems, API design, and typed architectures
  • Experience designing and operating scalable distributed or service-oriented systems in production environments
  • Hands-on experience building or operating AI infrastructure, orchestration systems, retrieval platforms, or modern RAG architectures in production
  • Strong understanding of distributed systems concepts including queues, event streams, retries, consistency models, concurrency, and fault tolerance
  • Active daily use and fluency with AI-assisted engineering workflows and agentic development tooling such as Claude Code, Cursor, or similar platforms, including effective use of LLMs throughout software design, implementation, debugging, and operational workflows.
  • Strong written and verbal communication skills with the ability to collaborate effectively across technical teams
  • Ability to operate independently in fast-moving, highly technical environments with evolving priorities
Preferred Qualifications:
  • Experience with orchestration and workflow frameworks such as LangGraph, Temporal, Celery, or similar technologies
  • Experience with vector databases, graph databases, search platforms, and modern retrieval architectures involving embeddings, hybrid search, reranking, or knowledge graph traversal
  • Experience with event-driven architectures, CDC pipelines, or streaming platforms such as Kafka, Pulsar, or pg-boss
  • Experience with observability and telemetry tooling such as OpenTelemetry, Prometheus, Grafana, or centralized logging platforms
  • Experience deploying and operating systems within regulated, high-security, hybrid-cloud, or air-gapped environments
  • Familiarity with secure software supply chain practices, signed artifact distribution, and multi-tenant platform isolation strategies
  • Contributions to internal developer platforms, reusable infrastructure tooling, or shared engineering frameworks
  • Experience mentoring engineers and contributing to engineering standards and architectural best practices
Education:
  • Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field preferred. Equivalent combinations of professional experience, technical training, certifications, or demonstrated expertise will also be considered.

Who thrives in this Role:

This team moves fast, operates with high autonomy, and builds things that don't exist yet. Engineers who do well here are genuinely deep in AI infrastructure, treat AI-assisted development as a core skill they're actively improving, and prefer building over debating. They own their outcomes without being pushed and find constrained, regulated environments interesting rather than frustrating.

If you've been building in this space on your own time and want to work somewhere that takes it seriously, this role is for you.

This role is not for you if...
  • You're drawn to AI but haven't actually built anything in the space.
  • You treat AI development tools as a novelty rather than a daily practice.
  • You do your best work with clear roadmaps, stable requirements, and plenty of process.
  • You want to architect and delegate rather than write the code yourself.
  • You need direction to get moving.
Employee Benefits:
  • Remote and Hybrid working environment
  • Competitive pay structure
  • Medical, dental, vision plans with employees covered up to 90% with highly progressive options for dependents and families
  • Company paid life, short- and long-term disability insurance
  • Employee Assistance Program
  • 401(k) match
  • Flexible Paid Time Off
  • Parental Leave
  • Access to thousands of Learning amp; Development courses that range from mental health and wellbeing, stress, and time management to an array of technical and business-related courses
Employment Perks:
  • We provide each employee with professional growth opportunities through succession planning, up-skilling, and certifications
  • Tuition and certification reimbursement
  • Employee Referral Programs
  • Company Sponsored Events
​Fortress is proud to be an Equal Opportunity Employer. All employees and applicants will receive consideration for employment without regard to age, color, disability, gender, national origin, race, religion, sexual orientation, gender identity, protected veteran status, or any other classification protected by federal, state, or local law. Fortress Information Security takes part in the E-Verify process for all new hires.

For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will have to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

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