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Senior Machine Learning Engineer Jobs in Texas (NOW HIRING)

webAI Inc

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments. You ...

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 ...

Roku

Senior Machine Learning Engineer

Austin, TX

$121K - $160K/yr

We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and ...

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 · 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 ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

We're looking for seasoned engineers with a background in machine learning to aid in this mission. Examples of problems include improving ad relevance, inferring demographics, yield optimization, and ...

SansuTek Inc.

Sr Machine Learning Engineer

Fort Worth, TX · On-site

$117K - $154K/yr

Mixed-Integer Programming (MIP)modeling; formulatingreal-world businessrules asdecision variables ... and deploy machine learning models, focusing on the technical aspects of model deployment.

PayPal

Sr Machine Learning Engineer

Austin, TX · On-site

$55.25 - $73/hr

... Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques ... , SR 11-7, OCC 2011-12, EU AI Act) is a plus. Subsidiary: PayPal Travel Percent: 0 - The base pay ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX · On-site

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for our advanced distributed processing platforms. This role is ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for our advanced distributed processing platforms. This role is ...

CesiumAstro

Senior Machine Learning Engineer II

Austin, TX

$103K - $142K/yr

We are looking for a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for our advanced distributed processing platforms. This role is ...

X4 Engineering

Machine Learning Engineer

Austin, TX · On-site

$140K - $180K/yr

🚀 Machine Learning Engineer 📍 Austin, TX (Hybrid/Remote Considered) 💰 $140,000 - $180,000 Base We're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Texas

Senior Machine Learning Engineer information

See Texas salary details

$55.4K

$117.9K

$171K

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

As of Jul 21, 2026, the average yearly pay for senior machine learning engineer in Texas is $117,907.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $133,700.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Texas? The most popular types of Machine Learning Engineer jobs in Texas are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Texas? For Senior Machine Learning Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Texas look for? The top searched job categories for Senior Machine Learning Engineer jobs in Texas are:
What cities in Texas are hiring for Senior Machine Learning Engineer jobs? Cities in Texas with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Texas as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $117,907 per year, or $56.7 per hour.

Senior Machine Learning Engineer

webAI Inc

Austin, TX • On-site

$103K - $142K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted yesterday

Job description

Special Notice:
This position is NOT contingent upon awarding of a project or needing a funding source. This is full-time employment with webAI.
About the Role:
We are seeking a Senior Machine Learning Engineer to support our Public Sector initiatives focused on building and optimizing production ready AI systems for secure and distributed environments.
You will be responsible for transforming prototype models into scalable, efficient, and reliable production systems that operate seamlessly across a spectrum of hardware from government cloud infrastructure to edge devices in restricted or disconnected environments.
Responsibilities:
  • Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems.
  • Productionize AI models from research prototypes into scalable, deployable systems used in real world applications.
  • Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.
  • Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific acceleration.
  • Build and maintain Retrieval Augmented Generation (RAG) pipelines, including vector database integration for contextual retrieval.
  • Work with multi-modal AI systems across computer vision, audio, and natural language domains.
  • Optimize model execution for distributed and resource constrained environments, ensuring reliability under variable connectivity conditions.

Qualifications:
  • Active US Security clearance
  • 4+ years of experience in applied AI, ML engineering, or production AI systems.
  • Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers.
  • Proven experience deploying AI models across cloud, edge, and mobile hardware environments.
  • Expertise in model compression and optimization (quantization, pruning, distillation).
  • Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone).
  • Familiarity with multi-modal models and synthetic data generation methods.
  • Strong algorithmic and problem solving skills, especially in distributed or constrained compute environments.

Preferred Skills:
  • Experience with edge AI, federated learning, or offline inference systems.
  • Understanding of AI governance and compliance frameworks relevant to public sector deployments.
  • Experience integrating models into large scale distributed systems or microservice architectures.
  • Excellent communication and technical documentation skills for collaboration across multi disciplinary teams.
  • Strong understanding of GPU computing, CUDA, and performance profiling.

We at webAI are committed to living out the core values we have put in place as the foundation on which we operate as a team. We seek individuals who exemplify the following:
  • Truth - Emphasizing transparency and honesty in every interaction and decision.
  • Ownership - Taking full responsibility for one's actions and decisions, demonstrating commitment to the success of our clients.
  • Tenacity - Persisting in the face of challenges and setbacks, continually striving for excellence and improvement.
  • Humility - Maintaining a respectful and learning-oriented mindset, acknowledging the strengths and contributions of others.

Benefits:
We strive to provide competitive benefits to all employees. The benefits listed in this posting generally apply to U.S.-based employees. For employees hired outside the United States, benefits may vary based on local law, country-specific requirements, and the employment platform or entity through which the employee is hired.
  • Competitive salary
  • Comprehensive health, dental, and vision benefits package
  • 401(k) match (U.S.-based employees only)
  • $200/month Health & Wellness stipend
  • Continuing Education support
  • $500/year Function Health subscription (U.S.-based employees only)
  • Free parking for in-office employees
  • Flexible Time Off (FTO)
  • Parental leave for eligible employees
  • Supplemental life insurance

webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.

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