Machine Learning Engineer

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Austin, TX
Employment: Full-time
Posted: 74 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $226k

$163k $290k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $200,437–$251,925.

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 43 open roles on FindRole.

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At a glance

TL;DR · Machine Learning Engineer

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The Machine Learning Engineer joins the team to provide hands-on expertise in designing, implementing, and scaling AI solutions. This role involves designing and implementing machine learning algorithms for various business applications, conducting research to advance capabilities, and developing scalable machine learning pipelines. The engineer will collaborate with cross-functional teams to integrate AI solutions into production environments while analyzing large datasets to extract meaningful insights. Key technical requirements include proficiency in Python, R, or Java, along with experience using ML frameworks like TensorFlow, PyTorch, and scikit-learn. Candidates must possess strong knowledge of statistics, optimization, probability theory, and experimental methodologies. The work focuses on applying a disciplined, banking-first approach to help shape how AI is utilized within the financial services industry.

What does a Machine Learning Engineer earn?

Median $235750 from 323 postings across 48 companies.

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Skills

Python R Java TensorFlow PyTorch scikit-learn Machine Learning AI Statistics Probability Theory Optimization

What you'll do

Design and implement machine learning algorithms and models for various business applications.
Conduct research and experimentation to advance 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.
Ensure the quality and performance of AI systems through rigorous testing and validation.
Maintain up-to-date knowledge of emerging AI and machine learning trends.

What we're looking for

Bachelor’s degree in a related field.
5–8 years of relevant experience.
Proven experience in ML 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/libraries such as TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms and scalable computing resources.
Authorization to work for any employer in the U.S.

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