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Applied Optimization Jobs in Texas (NOW HIRING)

Dialpad

Sr. Software Engineer, Applied AI Systems

Austin, TX · On-site

$121K - $160K/yr

Our Applied AI team develops models, agentic capabilities, and evaluation methods that power these ... Experience with service observability, debugging, performance optimization, and production incident ...

Oxy

AI Optimization Engineer

Houston, TX

Master's degree in Engineering, Applied Mathematics, or a related field. * Strong knowledge of optimization methods, including dynamic, parametric, and non-parametric approaches * Experience ...

Geico

Staff Engineer - Applied AI

Dallas, TX · On-site

GEICO is seeking a Staff Engineer, Applied AI to help shape how Generative AI enhances customer and ... Strong competency in distributed systems, service design, performance optimization, and reliability ...

Applied Materials

Business Unit Operations IV

Austin, TX · On-site

$116K - $159K/yr

Who We Are Applied Materials is the global leader in materials science and engineering solutions ... Drive Planning and Operational execution to ensure optimal Balance Sheet performance, including ...

Applied Materials

Business Unit Operations IV

Austin, TX

$116K - $159K/yr

Who We Are Applied Materials is the global leader in materials science and engineering solutions ... optimal Balance Sheet performance, including optimization of cash and Inventory Mgmt. Ensure OPEX ...

InterSources Inc

Applied AI Senior Engineer

Austin, TX · On-site

$103K - $142K/yr

InterSources Inc is seeking an Applied AI Senior Engineer to join their team. The role involves ... cost optimization, compute decisions, not just deployment • Hands-on with Docker and Kubernetes ...

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All JobsApplied Optimization JobsApplied Optimization Jobs in Texas

Applied Optimization information

What is the difference between Applied Optimization vs Data Analyst?

AspectApplied OptimizationData Analyst
Required CredentialsBachelor's in Operations Research, Industrial Engineering, or related fields; often certifications in optimization toolsBachelor's in Statistics, Mathematics, or related fields; certifications in data analysis tools
Work EnvironmentCorporate, manufacturing, logistics, or consulting firms focusing on process improvementBusiness, finance, healthcare, or marketing sectors analyzing data trends
Employer & Industry UsageUsed in industries requiring process optimization and resource allocationUsed across industries for interpreting data and supporting decision-making

Applied Optimization focuses on developing mathematical models to improve processes and resource use, often requiring specialized optimization skills. Data Analysts interpret data to identify trends and support strategic decisions. While both roles analyze data, Applied Optimization emphasizes mathematical modeling for operational improvements, whereas Data Analysts focus on data interpretation and reporting.

What jobs use applied optimization?

Applied optimization is used in roles such as operations researcher, data analyst, supply chain analyst, and industrial engineer. These jobs involve developing algorithms, modeling systems, and improving processes using mathematical and computational techniques to increase efficiency and reduce costs.

What are popular job titles related to Applied Optimization jobs in Texas?

For Applied Optimization jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Applied Optimization jobs in Texas look for?

The top searched job categories for Applied Optimization jobs in Texas are:

What cities in Texas are hiring for Applied Optimization jobs?

Cities in Texas with the most Applied Optimization job openings:

Applied Optimization jobs near you
Infographic showing various Applied Optimization job openings in Texas as of September 2026, with employment types broken down into 69% Full Time, and 31% Part Time. Highlights an 100% In-person job distribution.

Sr. Software Engineer, Applied AI Systems

Austin, TX • On-site

Dialpad
Telecommunications • 1 - 5K employees
Learn more about Dialpadexternal

$121K - $160K/yr

Full-time

Posted 6 days ago

Job description

Your role
Dialpad is building AI that helps businesses communicate, resolve customer needs, and automate work in real time. Our Applied AI team develops models, agentic capabilities, and evaluation methods that power these experiences.

As a Sr. Software Engineer, Applied AI Systems, you will build the software systems that power Dialpad's next-generation agentic AI. You will work closely with Applied Scientists and partner with engineering teams to turn advanced AI capabilities into reliable, scalable customer-facing experiences.

This is a hands-on role for an engineer who enjoys building agentic systems at the intersection of AI, backend services, and product delivery. You will help shape how DialpadGPT models are integrated, evaluated, monitored, and deployed in next-generation AI products, including real-time conversational experiences.

What you'll do

  • Design and build scalable backend services and distributed systems for agentic AI applications.
  • Partner with Applied Scientists to bring models, evaluation methods, and agentic capabilities from prototype to production.
  • Build software that connects models, tools, data, and evaluation feedback into robust AI experiences.
  • Develop APIs, data flows, and integration patterns for low-latency, high-quality AI services.
  • Build systems for model deployment, release management, monitoring, evaluation, and safe rollout.
  • Improve the reliability, latency, scalability, and cost efficiency of production AI systems.
  • Contribute to the evolution of DialpadGPT and the engineering systems that support next-generation agentic experiences.
  • Work across engineering, product, and research to resolve complex technical problems and deliver measurable customer impact.

What you'll bring

  • 5+ years of professional software engineering experience building and operating production services.
  • Strong experience with backend systems, distributed services, APIs, and cloud-based infrastructure.
  • Experience building agentic systems, LLM-powered applications, model-serving systems, or AI-enabled backend services in production.
  • Strong programming skills in Python and/or other backend languages, with a focus on clean, maintainable, well-tested code.
  • Experience with service observability, debugging, performance optimization, and production incident response.
  • Ability to work effectively in an ambiguous, fast-moving environment and translate technical prototypes into durable systems.
  • Strong communication and collaboration skills, especially when working with Applied Science, product, and engineering partners.

Apply