PROS Holdings, Inc.

Machine Learning Engineer II

PROS Holdings, Inc. • $100K — $140K *
US-AnywhereRemote in Houston, TX
Information Technology
5 - 7 years of experience
Reposted Today
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Job Overview by Ladders

Qualifications

  • 5+ years of experience in machine learning engineering or data-intensive software engineering.
  • Strong proficiency in Python and production-grade ML systems development.
  • Hands-on experience with distributed data and ML frameworks like PySpark and Databricks.
  • Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
  • Good understanding of distributed systems and performance optimization techniques.
  • Experience with deploying and maintaining ML models for various inference types.
  • Familiarity with Linux and cloud platforms, with a preference for Microsoft Azure.

Responsibilities

  • Design, implement, and productionize ML models and data pipelines with teams.
  • Convert research workflows into scalable and secure production systems.
  • Build and optimize distributed ML pipelines for large-scale tasks.
  • Apply ML best practices for model tuning and performance optimization.
  • Deploy, monitor, and troubleshoot ML systems in a production environment.
  • Evaluate and suggest improvements for existing ML pipelines.
  • Extend shared ML libraries for consistency and reuse.

Benefits

  • Flexible work environment with opportunities for remote work.
  • Active collaboration with a team of skilled professionals.
  • Potential for professional growth through advanced projects and learning.
  • Fostering a culture of innovation through AI-driven solutions.
  • Exposure to cutting-edge ML technologies and frameworks.
Full Job Description
Machine Learning Engineer II

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.


About PROS Holdings, Inc.

PROS Holdings, Inc. provides AI-powered solutions that optimize selling in the digital economy. The company's solutions enable companies to price, configure, and sell their products and services with speed, precision, and consistency across all sales channels. Its solutions include pricing optimization, sales effectiveness, and revenue management. The company serves customers in various industries, including automotive, manufacturing, food and beverage, healthcare, and airline. PROS Holdings, Inc. was founded in 1985 and is headquartered in Houston, Texas.
Learn more about PROS Holdings, Inc.
Size
1,545 employees
Market Cap
$1 billion
Industry
Consumer Technology
Net Income
-$76.9 million
5 Year Trend
+10.4%
Revenue
$252.4 million
NASDAQ
PRO
* Ladders Estimates

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