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Machine Learning Engineer Two Jobs in Texas (NOW HIRING)

Machine Learning Engineer II

Houston, TX ยท On-site

$93K - $127K/yr

Machine Learning Engineer II About PROS: PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue ...

Senior Machine Learning Engineer II

Austin, TX ยท On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for advanced distributed processing platforms, working ...

Senior Machine Learning Engineer II

Austin, TX ยท On-site

$103K - $142K/yr

They are seeking a Senior Machine Learning Engineer II to contribute to the development and deployment of machine learning solutions for advanced distributed processing platforms, collaborating ...

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Degree in Computer Science, Machine Learning, or Related disciplines; and 2+ years of relevant experience -Excellence in Python -Deep expertise in algorithms and data structures -Exposure to DevOps ...

Machine Learning Engineer LOCATIONSan Antonio, TX 78208 CLEARANCETS/SCI Full Poly (Please note this ... Some contracts give 2 years experience credit for a Master's Degree. We will work with you to find ...

Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI-enabled solutions that improve software delivery workflows, automate operational processes, and ...

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 ...

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 ...

Senior Machine Learning Engineer II

Austin, TX ยท 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 ...

Senior Machine Learning Engineer II

Austin, TX ยท 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 ...

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI ... space * 2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS ...

Machine Learning Engineer LOCATION San Antonio, TX 78208 CLEARANCE TS/SCI Full Poly (Please note ... Some contracts give 2 years experience credit for a Master's Degree. We will work with you to find ...

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Machine Learning Engineer Two information

Can you work for two engineering companies at the same time?

As a Machine Learning Engineer, working for two companies simultaneously is possible but depends on employment agreements, non-compete clauses, and company policies. Many employers require exclusivity or limit outside work to prevent conflicts of interest, especially if projects overlap or involve proprietary information. It is important to review employment contracts and disclose side work to ensure compliance.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine AI models and algorithms. Other roles that are expected to persist include healthcare professionals, skilled tradespeople, educators, and creative roles such as writers and designers, because these jobs require human judgment, empathy, or manual skills that are difficult for AI to replicate. Success in these fields often depends on specialized knowledge, critical thinking, and adaptability to new tools and technologies.

Will AI take over machine learning engineer jobs?

Machine Learning Engineers design and develop AI systems, and while AI automation can handle certain tasks, the role requires expertise in model development, data analysis, and problem-solving that AI cannot fully replace. Human oversight, creativity, and understanding of domain-specific challenges remain essential in the field.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
What cities in Texas are hiring for Machine Learning Engineer Two jobs? Cities in Texas with the most Machine Learning Engineer Two job openings:

Machine Learning Engineer II

PROS

Houston, TX โ€ข On-site

$93K - $127K/yr

Full-time

Posted 9 hours ago


Job description

Machine Learning Engineer II

About PROS:

PROS, Inc. is the leading offer management provider to the airline industry, helping airlines deliver seamless retail experiences designed to maximize revenue and margin growth. Powered by AI, the PROS Platform enables commercial teams to align capacity with demand and coordinate pricing, merchandising and offer strategies to construct and market optimal offers in real time. By optimizing every customer interaction, PROS helps airlines improve revenue performance and quality, increase commercial agility, attract more customers and build lasting loyalty. Learn more atpros.com.

Day in the Life of the Machine Learning Engineer II:

PROS is seeking a Machine Learning Engineer II to build, deploy, and operate scalable machine learning solutions within the PROS Platform. This role focuses on productionizing ML models, optimizing performance at scale, and owning well-defined ML components while collaborating closely with research scientists and software engineers. Design, implement, and productionize machine learning models and data pipelines in collaboration with data scientists and engineers.

  • Design, implement, and productionize machine learning models and data pipelines in collaboration with data scientists and engineers.
  • Convert research and prototype workflows into scalable, reliable, and secure production systems.
  • Build and optimize distributed ML pipelines for large-scale training and low-latency inference.
  • Apply ML best practices for feature engineering, model tuning, validation, and performance optimization.
  • Deploy, monitor, and maintain ML systems in production; diagnose and resolve performance and reliability issues.
  • Evaluate existing ML pipelines and recommend improvements to architecture, tooling, and processes.
  • Extend and optimize shared ML libraries and frameworks to support reuse and consistency.
  • Partner with software engineers to integrate ML solutions into the platform and meet SLA requirements.

Required Qualifications - About you:

  • 5+ years of progressively responsible experience (including time spent to pursue advanced degree) in machine learning engineering or data-intensive software engineering.
  • Strong proficiency in Python and experience building production-grade ML systems.
  • Hands-on experience with distributed data and ML frameworks such as PySpark, Databricks, and MLflow.
  • Experience with deep learning frameworks (TensorFlow and/or PyTorch).
  • Strong understanding of distributed systems, performance tuning, and cost optimization.
  • Experience deploying, monitoring, and maintaining ML models for batch and real-time inference.
  • Familiarity with Linux environments and cloud platforms, preferably Microsoft Azure.
  • Strong communication skills and ability to work independently on well-defined problems.

Highly Preferred:

  • Advanced degree in Computer Science, Machine Learning, Data Science, or a related field (PhD preferred).
  • Experience with GPU-accelerated training or inference.
  • Exposure to advanced ML techniques and large-scale optimization problems.
  • Experience improving shared ML platforms, tooling, or libraries used across teams.
  • Experience in pricing, revenue management and offer optimization.

AI Fluency & Growth Mindset - We welcome candidates who:

  • Understand core AI concepts and apply them ethically to enhance productivity, insights, and decision-making.
  • Craft effective prompts to optimize the quality and relevance of AI-generated outputs.
  • Explore and apply agentic AI systems, using or managing autonomous agents to streamline workflows and automate tasks.
  • Leverage AI tools to boost efficiency, creativity, and innovation in their daily work.
  • Stay curious and adaptable, continuously experimenting with AI-driven solutions to elevate team performance and customer impact.

Why Join PROS?

PROS culture and its extraordinary people are at the core of our success. We are passionate about what we do and relentless in delivering on our promises.

Our commitment to customer success inspires us to think smarter and dream bigger, empowering airlines to achieve more than they ever imagined through intelligent offer and revenue optimization.

At PROS, we foster a culture of care, where people feel supported to grow, innovate, and bring their best selves to work-every day. From flexible ways of working to continuous learning, we empower our teams to thrive both personally and professionally.

Join PROS, a dedicated travel technology company with nearly 40 years of proven airline expertise and a long runway for future growth, now powering the future of AI-driven airline retailing. If you want to be part of something exceptional, help us shape how airlines compete, innovate, and win.

PROS Core Values

  • We are Owners

We look for every opportunity to create a better PROS and a better experience for our customers - and we hold ourselves accountable.

  • We are Innovators

We think creatively to find new paths to success - for our people, our customers and our business.

  • We Care

We are centered on caring for the people, businesses, and communities we serve.