Machine Learning Engineer I

Reposted One Month Ago
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Sofia, Sofia-grad, BGR
In-Office
Entry level
Big Data • Software
The Role
Implement, scale, and maintain ML models and data pipelines; convert research prototypes into production; support feature engineering, model training, evaluation, deployment, monitoring, and debugging; collaborate with engineers and document code.
Summary Generated by Built In

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 at pros.com.

PROS is seeking a Machine Learning Engineer I to develop and support machine learning solutions within the PROS Platform. This role focuses on implementing, scaling, and maintaining ML components while learning to translate research prototypes into production systems in collaboration with senior engineers and data scientists. 

Day in the Life of the Machine Learning Engineer I:

  • Implement machine learning models and data pipelines based on guidance from senior engineers and scientists.  
  • Assist in converting research prototypes into reliable, scalable production workflows.
  • Support development of data pipelines and feature engineering workflows.
  • Contribute to model training, evaluation, and performance tuning.
  • Deploy and monitor ML models in batch and near real-time environments.
  • Debug issues in data pipelines and model performance with support from senior team members.
  • Write clean, maintainable, and well-documented code.
  • Collaborate with software engineers to integrate ML components into production systems. 

Required Qualifications - About you:

  • Degree in Computer Science, Statistics, Engineering, or related field (Masters preferred).
  • Experience in machine learning, data science, or related area (internships included).
  • Proficiency in Python  and familiarity with ML libraries (such as Numpy, Pandas, Scikit-learn).
  • Experience with deep learning frameworks (TensorFlow and/or PyTorch) and/or machine learning workflows.
  • Knowledge of core Machine Learning and AI models.
  • Strong problem-solving skills and willingness to learn. 

Highly Preferred:

  • Exposure to advanced ML techniques and large-scale optimization problems.
  • Experience deploying, monitoring, and maintaining ML models for batch and real-time inference. 
  • 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.


Skills Required

  • Degree in Computer Science, Statistics, Engineering, or related field (Bachelor's)
  • Master's degree preferred
  • Experience in machine learning, data science, or related area (internships included)
  • Proficiency in Python
  • Familiarity with ML libraries such as NumPy, Pandas, scikit-learn
  • Experience with deep learning frameworks (TensorFlow and/or PyTorch) and/or ML workflows
  • Knowledge of core Machine Learning and AI models
  • Strong problem-solving skills and willingness to learn
  • Exposure to advanced ML techniques and large-scale optimization problems
  • Experience deploying, monitoring, and maintaining ML models for batch and real-time inference
  • Experience in pricing, revenue management, and offer optimization
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The Company
HQ: Houston, TX
2,450 Employees
Year Founded: 1985

What We Do

PROS (NYSE: PRO) provides AI-based solutions that power commerce in the digital economy. Using artificial intelligence, PROS accelerates customers' ability to embrace digital selling and eCommerce channels. With predictive and prescriptive guidance, companies are enabled to dynamically price, configure and sell their products and services across all channels with speed, precision, and consistency. PROS customers, who are leaders in their markets, benefit from decades of data science expertise infused into our industry solutions. To learn more, visit pros.com

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