Machine Learning Engineer

3w3 weeks ago

Austin, US · Full-time · $140,000 – $180,000

About this role

Q2 is a leading provider of digital banking and lending solutions to banks, credit unions, alternative finance companies, and fintechs. The Machine Learning Engineer provides hands-on expertise in designing, implementing, and scaling AI solutions. Collaborate with cross-functional teams to advance machine learning capabilities and support business innovation.

Design and implement machine learning algorithms and models for various business applications. Conduct research and experimentation to advance machine learning capabilities. Analyze large datasets to extract meaningful insights and support data-driven decisions.

Being as passionate about our people as we are about our mission. Celebrate employees with “Circle of Awesomeness” award ceremony and day of employee celebration. Hold annual Dodgeball for Charity event at Q2 Stadium in Austin to build trust and collaboration.

Invest in the growth and development of team members through ongoing learning opportunities, mentorship programs, internal mobility, and meaningful leadership relationships. Foster a supportive, inclusive environment where career growth, collaboration, and wellness are prioritized. Offer resources for physical, mental, and professional well-being.

Requirements

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 (TensorFlow, PyTorch, scikit-learn)
Familiarity with cloud platforms and scalable computing resources
Strong analytical, problem-solving, and collaboration skills
Fluent written and oral communication in English
Authorized to work for any employer in the U.S.

Responsibilities

Design and implement machine learning algorithms and models for various business applications
Conduct research and experimentation to advance machine learning capabilities
Collaborate with cross-functional teams to integrate AI solutions into production environments
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

Benefits

Hybrid Work Opportunities
Flexible Time Off
Career Development & Mentoring Programs
Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave
Community Volunteering & Company Philanthropy Programs
Employee Peer Recognition Programs – “You Earned it”