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New Grad Machine Learning Jobs in Houston, TX (NOW HIRING)

Chevron

AI Engineer

Houston, TX · On-site

$93K - $127K/yr

Design and develop AI and Machine Learning solutions. * Design and develop agentic solutions ... Demonstrated ability to rapidly learn and apply new technologies, frameworks, and approaches in a ...

Chevron

AI Engineer

Houston, TX · On-site

Design and develop AI and Machine Learning solutions. * Design and develop agentic solutions ... Demonstrated ability to rapidly learn and apply new technologies, frameworks, and approaches in a ...

WorkNovas LLC

Senior Data Scientist

Houston, TX · On-site

This requires that you have next to your knowledge of machine learning and/or statistics a good ... Learning new engineering practices, technologies and continuously improving our Agile practices ...

Pwc

AI Engineer

Houston, TX · On-site

$50K - $112K/yr

... new technologies and methodologies in AI engineering What You Must Have - At least a Bachelor ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

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Showing results 41-60

All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Houston, TX

New Grad Machine Learning information

See Houston, TX salary details

$24.4K

$40.7K

$84K

How much do new grad machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for new grad machine learning in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What are popular job titles related to New Grad Machine Learning jobs in Houston, TX?

For New Grad Machine Learning jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching New Grad Machine Learning jobs in Houston, TX look for?

The top searched job categories for New Grad Machine Learning jobs in Houston, TX are:

What cities near Houston, TX are hiring for New Grad Machine Learning jobs?

Cities near Houston, TX with the most New Grad Machine Learning job openings:

New Grad Machine Learning jobs near you
Infographic showing various New Grad Machine Learning job openings in Houston, TX as of August 2026, with employment types broken down into 64% Full Time, and 36% Part Time. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $40,666 per year, or $19.6 per hour.

Senior Software Engineer

HP Development Company, L.P.

Spring, TX • On-site

$109K - $143K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 14 days ago

Job description

Senior Software Engineer
Description -
HP is seeking a Senior Software Engineer to help develop software platforms within HP's device and services ecosystem. This role will contribute to the design, implementation, integration, and validation of modern software experiences that span client applications, backend services, cloud integrations, device interfaces, and enterprise-ready workflows.
This role offers the opportunity to work in a start-up-like incubation environment within HP's PC Design team - moving quickly, solving ambiguous product challenges, and helping build new products that integrate edge AI into next-generation PC experiences. You will work closely with customers and cross-functional partners to understand real-world needs, incorporate feedback into product development, and help translate early concepts into scalable, production-quality software.
Ideal candidates should have demonstrated excellence e.g. successful shipped new products/features at scale, significant contributions to important open-source projects - in two or more of the following areas:
  • Large language models,

  • Computer vision models,

  • Speech recognition and synthesis,

  • Audio-video multimodal models

  • Human computer intelligent interactions

  • Deep neural networks

  • Model size reduction

  • Synthetic photorealistic image data generation

  • Robotics

  • Embedded systems

  • Cloud computing

  • AI Agents

  • Other relevant technologies (do tell us about them!)

This role requires strong technical judgment, practical problem-solving skills, and the ability to build reliable software in a fast-moving product development environment.
You will collaborate closely with cross-functional teams across software architecture, UX, product management, hardware engineering, security, manageability, validation, DevOps, systems engineering, and AI/ML engineering to deliver scalable, high-quality software capabilities.
Key Responsibilities
  • Design, develop, and maintain full-stack software features across frontend applications, backend services, local application components, cloud-connected workflows AI-enabled platform capabilities.

  • Integrate, evaluate, and deploy machine learning models - including LLMs, vision models, and audio models - into production software, covering data preprocessing, inference pipelines, evaluation, and monitoring.

  • Work with audio-video and multimodal models to enable capabilities such as meeting understanding, video summarization, audio-visual speaker attribution, and cross-modal search.

  • Fine-tune and adapt pre-trained models for product-specific use cases, and define the datasets, benchmarks, and quality metrics used to measure and improve them.

  • Design and implement agentic and retrieval-augmented (RAG) workflows that combine LLMs, tool use, and enterprise data sources.

  • Design, build, and evaluate agentic AI workflows - task decomposition, planning and reasoning loops, tool and function calling, memory and context management, and multi-agent orchestration - that automate real user workflows end to end.

  • Integrate machine learning models with cloud-based platforms and/or embedded systems for deployment in production environments.

  • Define guardrails, evaluation harnesses, and observability for agentic systems, including failure handling, human-in-the-loop checkpoints, cost and latency budgets, and reliability metrics.

  • Develop automated tests and contribute to CI/CD, build pipelines, code signing, packaging, and release readiness.

  • Stay updated with the latest advancements in machine learning, computer vision, robotics, and related fields to drive innovation within the organization.

  • Mentor junior team members and actively participate in knowledge sharing activities.

Education and Experience
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, Machine Learning, Mathematics, or equivalent practical experience.

  • 4-8 years of full-stack software development experience across frontend, backend, and application-level development.

  • Hands-on experience building, fine-tuning, or deploying machine learning models in production systems

Knowledge and Skills
  • Experience building modern frontend applications using technologies such as Angular, React, TypeScript, JavaScript, HTML, and CSS.

  • Backend development experience with one or more languages such as C++, Rust, Python, C#, Node.js, Go, or similar.

  • Experience integrating AI services, including LLMs and modern AI APIs.

  • Hands-on machine learning experience with frameworks such as PyTorch, TensorFlow / TensorFlow Lite, ONNX Runtime, or Hugging Face Transformers, including model inference, fine-tuning, and evaluation.

  • Experience designing multi-agent and long-running agentic pipelines with state management, retries, deterministic recovery, and evaluation of end-to-end task success.

  • Experience with LLMs, Vision Language, and speech models

  • Understanding of deep neural networks and model optimization techniques such as quantization, pruning, distillation, and model size reduction for edge and on-device deployment.

  • Experience deploying and serving models in cloud and edge environments (AWS, Azure, or Google Cloud, containerized inference, GPU/NPU acceleration).

  • Strong Python skills, with practical experience in data preprocessing, dataset creation, and model evaluation metrics.

  • Experience developing Windows desktop applications, APIs, and cloud-connected software.

  • Strong debugging, performance optimization, and software troubleshooting skills.

  • Experience with Git, CI/CD pipelines, automated testing, and modern software development practices.

  • Strong written and verbal communication skills with the ability to work effectively across global, cross-functional engineering teams.

Preferred
  • Experience with Tauri, WebView, WebRTC, PowerShell, COM, or native Windows development.

  • Experience with Microsoft Graph, Azure, Microsoft Intune, ADMX/Group Policy, or enterprise device management.

  • Experience building and deploying real-time and streaming audio pipelines - audio capture, resampling, chunking, buffering, WebSocket/gRPC streaming, and low-latency inference.

  • Experience with enterprise manageability solutions (MS Intune, ADMX/Group Policy, HP WXP or similar MDM/UEM platforms)

  • Experience building telemetry, diagnostics, resource monitoring, benchmarking, and test automation frameworks.

  • Experience with authentication, identity, SSO, and enterprise integrations.

  • Experience with LLM application patterns such as RAG, function/tool calling, agentic pipelines, and prompt/context optimization.

  • Experience running local or on-device inference on NPUs and accelerators (Windows ML/DirectML, OpenVINO, TensorRT, CoreML, or vendor NPU toolchains).

  • Experience with computer vision - object detection, OCR and document digitization, pose estimation, or depth/3D estimation.

  • Experience with speech synthesis (TTS), audio enhancement, or noise suppression.

  • Experience with MLOps tooling for experiment tracking, dataset versioning, model registries, and continuous model evaluation.

The pay range for this role is $165,450 to $259,750 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience.
Benefits:
HP offers a comprehensive benefits package for this position, including:
  • Health insurance
  • Dental insurance
  • Vision insurance
  • Long term/short term disability insurance
  • Employee assistance program
  • Flexible spending account
  • Life insurance
  • Generous time off policies, including;
  • 4-12 weeks fully paid parental leave based on tenure
  • 11 paid holidays
  • Additional flexible paid vacation and sick leave (US benefits overview)

The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.
Job -
Software
Schedule -
Full time
Shift -
No shift premium (United States of America)
Travel -
Relocation -
Equal Opportunity Employer (EEO) -
HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).
Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.
For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: "Know Your Rights: Workplace Discrimination is Illegal"

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