aimlroles

Senior ML Engineer

RTS Open · verified Oct 22, 2026
Addison Full-time Senior Machine Learning Engineering

At a glance

Senior Machine Learning Engineering role at RTS. Addison · full-time · no salary stated · we estimate $181,150–$247,500 across the United States.

Estimated pay

RTS has not published a salary for this role. The figure below is our estimate, not theirs.

$181,150 – $247,500
What the middle half of senior machine learning engineering roles in the United States paid, among postings that did state a salary.
Worked out from 330 postings that stated pay, median $213,425. Last updated Oct 22, 2026.
RoleMachine Learning Engineering
SenioritySenior
LocationAddison
EmploymentFull-time
PostedMar 18, 2026 · 7mo ago
Role brief

aimlroles summary, based on the employer's posting.

What you'll do

  • Create machine learning models and methods to solve business problems, then test ways to improve their results
  • Clean and examine large datasets, turning them into useful information for model work
  • Coordinate with data science and software engineering colleagues on scalable, efficient implementations
  • Launch models in production and watch their performance after release
  • Share your conclusions with stakeholders in clear, concise terms

What you bring

  • A bachelor's degree or above in computer science, engineering, mathematics or a related discipline
  • Two to five years of work in machine learning, data science or a related area
  • A GCP Professional Machine Learning Engineer certification
  • Programming skills in Python, Java or another listed language, and experience with a listed machine learning framework

Who this fits

This senior role suits someone ready to build and tune models, prepare data, and support production deployments. The position is based in Addison, United States of America.

From the employer

Responsibilities:
• Develop machine learning models and algorithms to address business needs.
• Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions.
• Clean, preprocess, and analyze large datasets to extract meaningful insights.
• Deploy machine learning models into production environments and monitor their performance.
• Continuously improve model accuracy and performance through experimentation and optimization.
• Stay up-to-date with the latest advancements in machine learning and related technologies.
• Communicate findings and results to stakeholders in a clear and concise manner.


Requirements:
• Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
• 2~5 years of experience in machine learning, data science, or a related field.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
• Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform.
• GCP Professional Machine Learning Engineer certification is required.
• Experience with version control systems such as Git.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.


Preferred Qualifications:
• Master's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
• Experience with distributed computing frameworks such as Apache Spark.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
• Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
• Experience with natural language processing (NLP) or computer vision (CV) techniques.
• Experience with continuous integration and continuous deployment (CI/CD) pipelines.
• Contributions to open-source projects or participation in relevant communities.