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Senior Machine Learning Scientist Jobs in Texas (NOW HIRING)

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer to transform prototype models into scalable, efficient, and reliable production systems that operate seamlessly across various hardware ...

Roku

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Bachelors, Masters, or PhD in Computer Science, Statistics, or a related field * 5 years of experience in applied machine learning on real use cases * Proficient coding skills and strong software ...

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 ... Bachelor's or higher degree in Computer Science, Engineering, or related technical field. * 6+ ...

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 ... Bachelor's or higher degree in Computer Science, Engineering, or related technical field. * 6+ ...

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 ...

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 ... Bachelor's or higher degree in Computer Science, Engineering, or related technical field. * 6+ ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · On-site

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Sr. Machine Learning Engineer

Richardson, TX · On-site

$94K - $129K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Apple

Sr. Machine Learning Engineer - Finance

Austin, TX

$184K - $277K/yr

Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.","responsibilities":"Build and operationalize AI ...

Apple

Sr. Machine Learning Engineer - Finance

Austin, TX

$184K - $277K/yr

Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.","responsibilities":"Build and operationalize AI ...

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

Senior Machine Learning Scientist information

See Texas salary details

$62K

$103K

$153.3K

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

As of Aug 10, 2026, the average yearly pay for senior machine learning scientist in Texas is $102,989.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,200.00 and $116,500.00 per year, depending on experience, location, and employer.

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

AspectSenior Machine Learning ScientistData Scientist
CredentialsMaster's or PhD in CS, ML, or related fieldBachelor's or Master's in CS, Statistics, or related field
Work EnvironmentFocus on developing ML models, algorithms, and researchData analysis, visualization, and business insights
Industry UsageUsed in AI-driven companies, tech firms, research labsCommon across industries for data analysis and reporting

While both roles involve working with data, Senior Machine Learning Scientists focus on developing advanced ML models and algorithms, often requiring research and deep technical expertise. Data Scientists typically analyze data to generate insights and support decision-making. The roles overlap but differ mainly in technical depth and focus area.

What is a senior machine learning scientist?

Senior Machine Learning Scientists are experienced professionals who design, develop, and implement advanced machine learning models to solve complex business or research problems. They are responsible for leading projects, mentoring junior team members, and staying updated on the latest AI and data science technologies. Their work often involves analyzing large datasets, selecting the right algorithms, and optimizing model performance for real-world applications. In addition to technical expertise, they often collaborate cross-functionally to align machine learning solutions with organizational goals.

What are the key skills and qualifications needed to thrive as a senior machine learning scientist?

To thrive as a Senior Machine Learning Scientist, you need expertise in machine learning algorithms, statistical analysis, programming (usually in Python or R), and an advanced degree (often a Ph.D.) in a quantitative field. Experience with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms, and version control systems is typically expected, along with knowledge of deploying models in production environments. Exceptional problem-solving, communication, and leadership skills help you translate complex data insights into actionable business solutions and mentor junior team members. These skills are crucial for developing innovative models, ensuring robust deployment, and driving impactful data-driven decisions.

What are some common challenges senior machine learning scientists face when deploying models to production environments?

Senior Machine Learning Scientists often encounter challenges such as ensuring model scalability, maintaining model performance over time, and addressing data drift once models are deployed to production. Collaborating closely with engineering and operations teams is crucial to streamline deployment pipelines and monitor models for real-world reliability. It’s also important to communicate findings and potential risks to stakeholders, and to regularly update models based on new data or business requirements. These aspects make strong cross-functional teamwork and problem-solving skills essential in this role.
What are the most commonly searched types of Machine Learning Scientist jobs in Texas? The most popular types of Machine Learning Scientist jobs in Texas are:
What are popular job titles related to Senior Machine Learning Scientist jobs in Texas? For Senior Machine Learning Scientist jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Scientist jobs in Texas look for? The top searched job categories for Senior Machine Learning Scientist jobs in Texas are:
What cities in Texas are hiring for Senior Machine Learning Scientist jobs? Cities in Texas with the most Senior Machine Learning Scientist job openings:
Senior Machine Learning Scientist jobs near you
Infographic showing various Senior Machine Learning Scientist job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 20% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $102,989 per year, or $49.5 per hour.

Senior Machine Learning Engineer

webAI

Austin, TX • On-site

$103K - $142K/yr

Full-time

Re-posted 22 days ago

Job description

Job Summary:
webAI is a company focused on building and optimizing production-ready AI systems for secure and distributed environments. They are seeking a Senior Machine Learning Engineer to transform prototype models into scalable, efficient, and reliable production systems that operate seamlessly across various hardware 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:
Required:
• 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:
• 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.
Company:
The leader in private AI. Founded in 2020, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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