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Senior Full Stack Machine Learning Engineer Jobs in Spring, TX

1 point system

Sr. Full-Stack

Houston, TX · On-site

Requirement - Sr. Full-Stack C# .NET Developer - Angular, (AI/Platform-leaning) Location- Houston ... Strong Full Stack Engineering experience * Backend development in C#, .NET, or similar (less ...

Medium

Senior Full Stack Software Engineer

Houston, TX · On-site

$172.20 - $206.64/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for an experienced Senior Full Stack Software Engineer to join our dynamic and growing team. In this role, you will play a pivotal part in designing, building, and maintaining scalable ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine ... • Own the full data science lifecycle on assigned projects: data sourcing and cleaning ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... and senior management * Genuine intellectual curiosity about commodities markets, global energy ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... and senior management * Genuine intellectual curiosity about commodities markets, global energy ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... and senior management * Genuine intellectual curiosity about commodities markets, global energy ...

myDNA, Inc.

Senior Full Stack Developer (Agentic AI)

Houston, TX · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Position Overview We are seeking a Senior Full Stack Developer (Agentic AI) to join our engineering ... Learning Agility: A proactive learner who stays current with the rapidly evolving AI landscape and ...

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must-Have (Technical Expertise & Core Responsibilities) * Deep Neural Networks (DNN): * Hands-on ...

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All JobsFull Stack Machine Learning Engineer JobsSenior Full Stack Machine Learning Engineer JobsSenior Full Stack Machine Learning Engineer Jobs in Spring, TX

Senior Full Stack Machine Learning Engineer information

See Spring, TX salary details

$39.6K

$119.9K

$169.5K

How much do senior full stack machine learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for senior full stack machine learning engineer in Spring, TX is $119,931.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,800.00 and $140,600.00 per year, depending on experience, location, and employer.

What is the difference between Senior Full Stack Machine Learning Engineer vs Data Scientist?

AspectSenior Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Data Science, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops end-to-end ML applications, integrates backend and frontendAnalyzes data, builds models, visualizes insights
Industry UsageTech, finance, healthcare, where deploying ML models is essentialResearch, analytics, consulting across various sectors

While both roles involve working with data and machine learning, the Senior Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, including frontend and backend integration. In contrast, Data Scientists primarily analyze data and develop models to generate insights. The engineer's role is more application-oriented, whereas the Data Scientist's role is more research and analysis-focused.

What cities near Spring, TX are hiring for Senior Full Stack Machine Learning Engineer jobs?

Cities near Spring, TX with the most Senior Full Stack Machine Learning Engineer job openings:

Senior Full Stack Machine Learning Engineer jobs near you

Sr. Full-Stack

1 point system

Houston, TX • On-site

Contractor

Re-posted 7 days ago

Job description

Requirement - Sr. Full-Stack C# .NET Developer - Angular, (AI/Platform-leaning)

Location- Houston, TX

Contract W2

Requirements:

  • Strong Full Stack Engineering experience
  • Backend development in C#, .NET, or similar (less concerned about the actual programming languages and frameworks as AI code generation can translate between languages/frameworks).
  • Frontend skills in Angular and/or React - their front-ends fluctuate between both.
  • Experience with component-based, modular architecture
  • Familiarity with:
    • AI/LLM concepts and integration into applications
    • RAG patterns or chatbot development
  • Understanding of Azure ecosystem basics (especially pipelines and services)

Domain

  • Experience working in Microsoft-centric environments
  • Exposure to AI/ML or LLM-based applications
  • Understanding of software engineering lifecycle and platform development

Soft Skills

  • Strong communication skills (English fluency required)
  • Ability to be flexible/fungible across teams
  • Quick ramp-up capability (2-week evaluation threshold)
  • Strong collaboration and adaptability

Engagement Overview

  • Project / Initiative: AI Foundation Program (post-moonshot stabilization and standardization)
  • Business Objective:
    • Establish foundational AI and engineering capabilities
    • Standardize development patterns (RAG, chatbot frameworks)
    • Enable scalable, reusable AI solutions across the organization
  • Current State / Problem:
    • Initial AI efforts (“moonshots”) executed without proper foundational architecture
    • Lack of standardized components, patterns, and processes
    • Multiple teams require support with inconsistent needs and maturity levels
  • Desired Outcome:
    • Centralized, repeatable AI engineering framework
    • Modular, component-based architecture for reuse
    • Well-defined SDLC practices
    • Reliable, high-quality engineering talent embedded across teams

Role Summary

  • Role Title: Full Stack Engineer (AI/Platform-leaning)
  • Reason for Opening:
    • Staff augmentation to support AI foundation buildout
    • Multiple teams need additional resourcing at varying skill levels
  • How this role fits into the broader project:
    • Core contributors to building reusable AI components, frameworks, and patterns
    • Support both application enablement and platform standardization
  • Team Structure / Reporting Line:
    • Distributed across teams under:
      • Josh (focus: software engineering / SDLC modernization)
      • Sam (focus: AI Foundry / agent-based systems)

Preferred Skills (Nice-to-Haves)

  • Experience with:
    • Azure AI services (e.g., Azure AI Search)
    • AI orchestration frameworks (e.g., Semantic Kernel, LangChain, AutoGen)
    • Agent-based architectures / “Agentic AI”
  • Experience building internal platforms or developer frameworks
  • Exposure to model management and automation pipelines
  • Familiarity with memory integration patterns in AI systems
  • Experience working in nearshore/distributed teams

Requirements:

  • Strong engineering foundation (Full Stack or Backend-oriented)
  • Experience integrating AI/LLM capabilities into applications
  • Hands-on experience developing:
    • RAG applications
    • Chatbots
    • Agentic workflows
    • AI-powered developer platforms
  • Understanding of prompt orchestration and AI application architecture
  • Experience building reusable AI patterns and frameworks
  • Experience with Azure AI Foundry
  • Knowledge of hosted agents and agent orchestration
  • Understanding of model management and automation
  • Experience integrating memory components into AI system
  • LLM lifecycle management, agentic architectures, RAG
  • Tool calling and workflow orchestration.
  • Evaluation, testing, and governance of AI systems
  • AI enablement and educating development teams on AI fundamentals

Experience creating reusable AI accelerators and reference architectures nice to have