ZipRecruiter

Log In

1

E Learning Developer Jobs in Spring, TX (NOW HIRING)

Cisco

Principal Machine Learning Engineer

Houston, TX

$291K - $369K/yr

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Pivotal Solutions

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Expertise in AI/ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and the end-to ... Strong programming skills in Python and proficiency with relevant libraries (e.g., NumPy, Pandas ...

NRG Energy

Sr. Instructional Designer

Houston, TX · On-site

Evaluate and pilot emerging AI authoring platforms and tools (e.g., AI-driven voiceover, avatar tools, adaptive learning engines) for team adoption. * Apply prompt engineering and AI-assisted content ...

E Tech Group

Senior DCS/PLC Engineer

Houston, TX

$99K - $130K/yr

We're one of the largest engineering and system integration firms in the United States providing ... Learning and growth are key parts of the E Tech culture. We provide you with training and ...

next page

Showing results 1-20

People also search for

All JobsE Learning Developer JobsE Learning Developer Jobs in Spring, TX

E Learning Developer information

See Spring, TX salary details

$16

$34

$45

How much do e learning developer jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for e learning developer in Spring, TX is $34.21, according to ZipRecruiter salary data. Most workers in this role earn between $29.09 and $38.08 per hour, depending on experience, location, and employer.

What is an E-Learning Developer job?

An E-Learning Developer is responsible for designing, developing, and implementing online learning materials and courses. They use instructional design principles, multimedia tools, and e-learning software to create engaging and interactive content. Their role often involves collaborating with subject matter experts, graphic designers, and other stakeholders to ensure effective learning experiences. Additionally, they may be responsible for maintaining and updating e-learning content to keep it relevant and accessible.

What Does an eLearning Developer Do?

As an eLearning developer, you design and implement the structure of online courses using eLearning tools, such as instructional software and applications. You take the blueprint for the course, including content that has been created by an instructional developer, and design and code the lessons. Your duties and responsibilities are to make the lessons visually appealing and engaging while effectively conveying the lessons to students or users. As an eLearning developer, you may work for an education company or a company that designs instructional tools and solutions for employee training.

What are the key skills and qualifications needed to thrive in the E Learning Developer position, and why are they important?

To thrive as an E Learning Developer, you need expertise in instructional design, multimedia creation, and a solid understanding of adult learning principles, typically supported by a relevant degree like instructional technology or education. Familiarity with Learning Management Systems (LMS) such as Moodle or Canvas, authoring tools like Articulate Storyline or Adobe Captivate, and experience with SCORM or xAPI standards are highly valuable. Strong project management, creative problem-solving, and effective communication skills help you collaborate and translate complex subjects into engaging online content. These competencies are critical for creating high-quality, impactful learning experiences that meet organizational and learner goals.

What are some common challenges E Learning Developers face in this role?

E Learning Developers often encounter challenges such as adapting content to suit diverse learners, ensuring accessibility compliance, and keeping up with rapidly evolving educational technologies. They may need to collaborate closely with subject matter experts who have varying levels of familiarity with digital tools, making clear communication essential. Managing tight project deadlines while maintaining high engagement and interactivity standards can also be demanding. However, overcoming these common challenges can be highly rewarding, as it directly contributes to the effectiveness and reach of educational programs.

More about E Learning Developer jobs
What are popular job titles related to E Learning Developer jobs in Spring, TX? For E Learning Developer jobs in Spring, TX, the most frequently searched job titles are:
What job categories do people searching E Learning Developer jobs in Spring, TX look for? The top searched job categories for E Learning Developer jobs in Spring, TX are:
What cities near Spring, TX are hiring for E Learning Developer jobs? Cities near Spring, TX with the most E Learning Developer job openings:
E Learning Developer jobs near you
Infographic showing various E Learning Developer job openings in Spring, TX as of June 2026, with employment types broken down into 2% Internship, 82% Full Time, 4% Part Time, and 12% Contract. Highlights an 72% In-person, 10% Hybrid, and 18% Remote job distribution, with an average salary of $71,153 per year, or $34.2 per hour.
Senior Machine Learning Engineer - Agentic AI

Senior Machine Learning Engineer - Agentic AI

MD Anderson Center

Houston, TX • On-site

$99K - $137K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 24 days ago

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 164 frontline employees who took The Breakroom Quiz

34th of 870 rated healthcare providers

Job description

As a Senior Machine Learning Engineer - Agentic AI within Data Impact & Governance, you will be at the forefront of designing and operating the platform capabilities that enable autonomous and semi-autonomous AI systems to function reliably across clinical, research, and operational domains.
This role offers a rare opportunity to build enterprise-wide agentic AI platforms in a regulated healthcare environment-where correctness, safety, governance, and auditability matter as much as innovation and scale. You will influence technical standards, platform architecture, and operational safeguards that shape how agentic AI is adopted across one of the world's leading cancer centers.
What's in it for you?
  • Outstanding Benefits: MD Anderson offers paid medical benefits, generous paid time off (PTO), and strong retirement plans, providing stability and long-term financial security.
  • Enterprise-Level Impact: Architect platform capabilities that support AI agents operating across complex health IT systems and enterprise workflows.
  • Technical Leadership: Shape standards, integration patterns, and guardrails governing agentic AI at organizational scale.
  • Career Growth & Visibility: Partner closely with enterprise architects, applied MLEs, data scientists, IT, and governance leaders on high-impact AI initiatives.
  • Responsible AI Innovation: Work in a mission-driven institution where responsible AI, safety, and trust are central to technology strategy.
  • Collaborative Culture: Join a highly skilled team that values intellectual rigor, mentorship, and cross-disciplinary collaboration.

***The ideal candidate will have a healthcare background with at least 5 years of industry experience in data science and 3+ years as a Senior ML Engineer focused agentic AI systems***
Summary
The Senior Machine Learning Engineer - Agentic AI designs, evolves, and operates enterprise-scale agentic AI platform capabilities that enable safe, scalable, and governed deployment of autonomous and semi-autonomous AI systems. The role focuses on platform architecture, interoperability, validation frameworks, and operational safeguards that allow internal and third-party agent systems to function reliably in production healthcare environments.
This position operates at the intersection of autonomous AI behavior, enterprise systems integration, and regulated healthcare operations-where subtle failures can have systemic and high-impact consequences.
Major Work Activities
Core Responsibilities
  • Lead the design, evolution, and operation of the enterprise agentic AI platform in collaboration with enterprise architects and platform ML engineers.
  • Build platform components that enable interoperability between first-party and third-party agents, including identity, state, memory, tool access, orchestration, auditability, and policy enforcement.
  • Define and document standardized integration patterns connecting agents with enterprise business systems, data platforms, APIs, and health IT systems.
  • Provide reusable platform services, reference implementations, and SDKs that reduce risk and accelerate delivery for applied teams.
  • Design and operate validation and de-risking frameworks, including simulation, sandboxing, shadow execution, canary releases, and continuous behavior monitoring.
  • Establish and enforce platform standards for agent development, including interfaces, execution contracts, evaluation hooks, safety constraints, and observability requirements.
  • Participate in platform governance, release coordination, and incident response, supporting investigation and remediation of agent-related failures.
  • Implement platform safeguards such as fallback mechanisms, rollback strategies, approval gates, rate limiting, audit trails, and kill-switch capabilities.
  • Partner with software engineering, security, IT, and health IT stakeholders to deploy agentic AI capabilities in secure enterprise environments.
  • Support responsible AI practices through traceability of prompts, policies, tools, models, agent actions, and documentation of known failure modes and limitations.

Competencies
Technical Expertise
  • Experience building AI or ML platforms that serve multiple downstream teams and production workloads.
  • Strong proficiency in Python and integration of modern ML frameworks (e.g., PyTorch) with large language models and agent systems.
  • Hands-on experience with agentic AI frameworks such as LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or equivalent.
  • Working knowledge of agentic AI protocols and interoperability standards (e.g., MCP, agent-to-agent communication, structured tool invocation).
  • Experience implementing planner-executor loops, hierarchical agents, and multi-agent coordination patterns.
  • Familiarity with workflow orchestration tools (Airflow, Prefect, Temporal) and distributed execution frameworks (Ray or equivalent).
  • Experience deploying containerized AI platforms using Kubernetes in enterprise cloud environments with lineage, auditability, and controlled promotion to production.

Analytical Expertise
  • Ability to reason at the systems and platform level, balancing safety, performance, flexibility, and usability.
  • Experience designing quantitative evaluation strategies for agentic systems, including success rates, latency, cost, recovery behavior, and safety metrics.
  • Strong understanding of enterprise data governance, security, and privacy requirements, including healthcare and health IT considerations.
  • Ability to identify systemic risks stemming from agent autonomy, non-determinism, tool access, and multi-agent interactions.
  • Experience analyzing failure modes caused by prompt drift, model updates, tool changes, and cross-system dependencies.

Oral & Written Communication
  • Collaborate effectively with architects, applied MLEs, data scientists, software engineers, and IT partners.
  • Produce clear documentation covering platform architecture, APIs, integration patterns, validation frameworks, and operational runbooks.
  • Communicate platform capabilities, risks, and limitations to leadership and partner teams.
  • Contribute to internal standards and shared practices that improve safety, scalability, and consistency of agentic AI development.
  • Provide hands-on technical guidance, mentorship, and troubleshooting support to platform adopters.
  • Present technical and non-technical concepts clearly in meetings and institutional forums.

Education Required: Bachelor's degree in Computer Science, Software Engineering, Data Science, Physics, Math & Statistics, or another related engineering discipline.
Preferred Education: Master's degree or PHD with a concentration in Science, engineering, or related field.
Experience Required: Five years of experience in machine learning engineering, data science, data engineering, and/or software engineering. With Master's degree, three years' experience required. With PhD, one year of experience required.
Preferred Experience:
  • Experience designing, deploying, and maintaining agentic AI systems that operate autonomously and collaboratively across distributed environments.
  • Experience in monitoring and troubleshooting autonomous agents post-deployment, including performance degradation, clinical incidents, model updates, or corrective actions.
  • Experience raising the technical bar for team members, such as establishing reproducibility practices, review standards, or shared patterns.
  • Experience technically evaluating third-party agentic AI platforms within clinical workflows.

The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

What MD Anderson Cancer Center employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply