Machine Learning Engineer II

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.

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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 product ionizing ML models, optimizing performance at a scale, and owning well‑defined ML components while collaborating closely with data scientists and software engineers.

• Design, implement, and product ionize 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.

• 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 (Tensor Flow 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.

• Advanced degree in Computer Science, Machine Learning, Data Science, or a related field.
• 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.

• 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.

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…