Machine Learning Engineer

Q2

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Austin, TX
Posted
28 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $223k
$165k most similar roles pay here $276k

This listing doesn't post a salary. Most similar roles pay $192,050–$254,750.

Based on 240 similar postings.

Employer

About Q2

Q2 Holdings is a cloud-based banking software company providing digital banking solutions to banks, credit unions, and alternative financial companies, including consumer and business banking platforms. Industry: Financial Technology & Digital Banking

Q2 currently has 31 open roles on FindRole.

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At a glance

TL;DR · Machine Learning Engineer

The Machine Learning Engineer joins a team focused on designing, implementing, and scaling AI solutions while collaborating with cross-functional teams to advance machine learning capabilities and support business innovation. This role involves developing machine learning algorithms for various applications, conducting research to advance capabilities, and building scalable pipelines and systems. The candidate will analyze large datasets to extract insights, ensure the quality of AI systems through testing, and maintain knowledge of emerging trends. Required technical skills include proficiency in Python, R, or Java, along with experience using frameworks like TensorFlow, PyTorch, and scikit-learn. Candidates must also possess a strong foundation in statistics, optimization, probability theory, and experimental methodologies while utilizing cloud platforms and scalable computing resources to solve complex problems within the financial services sector.

What does a Machine Learning Engineer earn?

Median $236000 from 319 postings across 54 companies.

See salary data

What you'll do

  • Design and implement machine learning algorithms and models for various business applications.
  • Conduct research and experimentation to advance internal machine learning capabilities.
  • Integrate AI solutions into production environments in collaboration with cross-functional teams.
  • Analyze large datasets to extract meaningful insights and support data-driven decisions.
  • Develop scalable machine learning pipelines and systems.
  • Maintain up-to-date knowledge of emerging AI and machine learning trends.
  • Ensure the quality and performance of AI systems through testing and validation.

What we're looking for

  • Bachelor's degree in a related field.
  • 5–8 years of relevant experience.
  • Proven experience in machine learning model development and deployment.
  • Strong knowledge of statistics, optimization, probability theory, and experimental methodologies.
  • Proficiency in programming languages such as Python, R, or Java.
  • Experience with ML frameworks including TensorFlow, PyTorch, and scikit-learn.
  • Familiarity with cloud platforms and scalable computing resources.
  • Authorization to work for any employer in the U.S.

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