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Remote Machine Learning Jobs in Highlands, TX (NOW HIRING)

SupplyHouse

Senior Product Manager

Houston, TX · Remote

$109K - $137K/yr

This is a remote-based role within select states in the United States. At this time, we are only ... Identifies and prioritizes opportunities to apply AI and machine learning -- such as dynamic ...

Imubit

Financial Controller

Houston, TX · On-site +1

Imubit is looking for a top-notch Financial Controller to help disrupt the manufacturing world with breakthrough machine learning technologies. This role is open to remote candidates in the US.

Huntington

Lead Decision Analyst: Onsite

Houston, TX · On-site +1

... machine learning, statistics and text mining techniques * Experience with Business Intelligence ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Lead Decision Analyst: Onsite

Houston, TX · On-site +1

... machine learning, statistics and text mining techniques * Experience with Business Intelligence ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Quvia

Sales Engineer, Energy

Houston, TX · On-site +1

Our platform uses AI and machine learning to orchestrate connectivity across satellite, terrestrial ... We are headquartered in the greater Miami region, with remote teams spanning the U.S., Europe, and ...

Quvia

Sales Engineer, Energy

Houston, TX · Remote

Our platform uses AI and machine learning to orchestrate connectivity across satellite, terrestrial ... We are headquartered in the greater Miami region, with remote teams spanning the U.S., Europe, and ...

Hewlett Packard Enterprise

AI System Architect

Houston, TX · On-site +1

$232K/yr

AI System Architect This role has been designated as 'Remote/Teleworker', which means you will ... HPC & AI Business Unit - AI System Architect Distinguished Technologist. - AI & Machine Learning ...

Crowe LLP

Senior AI Engineer

Houston, TX · On-site +1

$99K - $137K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

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Showing results 41-60

All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Highlands, TX

Remote Machine Learning information

See Highlands, TX salary details

$22.3K

$37.3K

$77K

How much do remote machine learning jobs pay per year?

As of Jul 25, 2026, the average yearly pay for remote machine learning in Highlands, TX is $37,256.00, according to ZipRecruiter salary data. Most workers in this role earn between $28,400.00 and $40,200.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Highlands, TX? The most popular types of Machine Learning jobs in Highlands, TX are:
What cities near Highlands, TX are hiring for Remote Machine Learning jobs? Cities near Highlands, TX with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you

Platform Engineer - AI & Automation Platform

Inizio Partners

Houston, TX • Remote

Full-time

Posted 3 days ago

Job description

Role: Platform Engineer – AI & Automation Platform

Location: Remote

Type: Contract (Long term)

Role Summary: We are seeking a highly technical Platform Engineer focused on AI, automation, and platform enablement to help scale a governed, AI-accelerated engineering ecosystem across Power Platform, Dynamics 365, Azure, AWS, and enterprise digital applications. This role is responsible for building, operating, and advancing the shared platform capabilities that product teams depend on to deliver secure, scalable, AI-enabled solutions. The engineer will help drive platform reliability, AI enablement, automation, CI/CD modernization, observability, and developer acceleration across the SDLC. The ideal candidate combines strong platform engineering fundamentals with hands-on experience in automation, AI-assisted development workflows, cloud platforms, APIs, integrations, and enterprise delivery tooling.

Key Responsibilities

  • Build, manage, and evolve shared platform engineering capabilities across Power Platform, Dynamics 365 F&O, Azure, AWS, APIs, integrations, and digital applications
  • Support and operationalize AI-enabled development workflows including local agents, Copilot-assisted engineering, orchestration services, and automated SDLC pipelines
  • Design and maintain CI/CD pipelines, deployment automation, environment strategies, release controls, and platform governance standards
  • Implement reusable platform services, automation frameworks, connectors, templates, shared components, and developer acceleration tooling
  • Support AI and automation lifecycle capabilities including Power Platform Copilot Studio, M365 Copilot integrations, Azure AI Foundry, machine learning workflows, and agent orchestration patterns
  • Build and support platform observability including telemetry, logging, monitoring, alerting, tracing, and operational dashboards
  • Support automated quality engineering practices including pipeline validation, regression execution, automated testing integration, and release gating
  • Implement and operationalize platform security controls including RBAC, managed identities, API security, secrets management, DLP policies, audit logging, and environment governance
  • Partner with Enterprise Architecture, Cybersecurity, Cloud Engineering, and Data & AI teams to align implementations with enterprise standards and governance requirements
  • Support AI governance practices including behavioral monitoring, agent lifecycle controls, Responsible AI enforcement, risk evaluation, and operational review processes
  • Assist product and engineering teams with platform onboarding, automation adoption, environment provisioning, troubleshooting, and platform optimization
  • Drive platform reliability, resiliency, scalability, and operational excellence across shared engineering services
  • Contribute to developer experience improvements through automation, self-service tooling, standardized patterns, and reusable engineering assets
  • Support cost optimization, performance tuning, and operational efficiency initiatives across cloud and platform services

Required Qualifications

  • 8+ years of experience in Platform Engineering, Cloud Engineering, DevOps, Automation Engineering, or related enterprise engineering roles
  • Hands-on experience with Microsoft Power Platform, Dataverse, Dynamics 365 F&O, Azure services, and enterprise integrations
  • Experience building and supporting CI/CD pipelines using Azure DevOps, GitHub, or similar platforms
  • Experience with infrastructure automation, deployment scripting, environment management, and configuration management
  • Strong understanding of APIs, integrations, authentication, OAuth, REST services, and enterprise integration patterns
  • Experience supporting cloud-native and hybrid architectures across Azure and AWS
  • Experience with observability tooling, monitoring platforms, telemetry pipelines, and operational diagnostics
  • Experience with AI-enabled engineering workflows, Copilot technologies, LLM integrations, automation tooling, or agentic workflows
  • Strong understanding of platform security, governance, operational controls, and enterprise engineering standards
  • Experience supporting agile product delivery teams in large enterprise environments
  • Strong troubleshooting, automation, and systems thinking capabilities

Preferred Qualifications

  • Experience with Power Platform Copilot Studio, Azure AI Foundry, Azure OpenAI, or enterprise AI enablement platforms
  • Experience supporting AI orchestration, MCP-based integration patterns, automation agents, or AI-assisted SDLC workflows
  • Experience with automated testing frameworks, Playwright, pipeline-based quality enforcement, or test automation platforms
  • Experience with containerization, serverless architectures, and modern cloud platform services
  • Experience with Application Insights, Log Analytics, Power BI operational reporting, or enterprise telemetry platforms
  • Familiarity with SOX controls, audit readiness, operational governance, and regulated enterprise environments

Core Competencies

  • Microsoft Power Platform
  • Dataverse
  • Dynamics 365 Finance & Operations
  • Azure Services
  • AWS Services
  • Azure DevOps
  • GitHub
  • REST APIs & Integrations
  • Power Platform Copilot Studio
  • M365 Copilot
  • Azure AI Foundry
  • CI/CD & Automation Tooling
  • Observability & Monitoring Platforms
  • Automated Testing & Quality Engineering Tooling