ABOUT OPORTUN

Oportun (Nasdaq: OPRT) is a digital banking platform that puts its 1.9 million members' financial goals within reach. With intelligent borrowing, savings, budgeting, and spending capabilities, Oportun empowers members with the confidence to build a better financial future. Since inception, Oportun has provided more than $15.5 billion in responsible and affordable credit, saved its members more than $2.3 billion in interest and fees, and helped our members save an average of more than $1,800 annually. For more information, visit Oportun.com.

 

WORKING AT OPORTUN


Working at Oportun means enjoying a differentiated experience of being part of a team that fosters a diverse, equitable and inclusive culture where we all feel a sense of belonging and are encouraged to share our perspectives. This inclusive culture is directly connected to our organization's performance and ability to fulfill our mission of delivering affordable credit to those left out of the financial mainstream. We celebrate and nurture our inclusive culture through our employee resource groups.

POSITION OVERVIEW:

We are seeking a seasoned and accomplished Principal Machine Learning Engineer to lead and shape the development of our end-to-end ML infrastructure, from model conception and training to seamless deployment. By joining our accomplished team, you will play a pivotal role in driving the delivery of advanced, impactful, and transformative solutions will have a profound impact on the lives of millions of underserved individuals.

As the Principal Machine Learning Engineer at Oportun, you will take on a leadership role to architect, design, and execute the development of our comprehensive ML infrastructure. Working closely with cross-functional teams, including data scientists, software engineers, and product managers, you will spearhead the creation of scalable, efficient, and cutting-edge machine learning solutions that consistently exceed performance and reliability benchmarks. Your profound expertise in building and deploying complex machine learning models will be instrumental in the realization of our products full potential.

RESPONSIBILITIES:

  • Define and execute a visionary roadmap for building a robust and scalable ML infrastructure, encompassing all aspects from model development to deployment.
  • Lead, mentor, and collaborate with a team of machine learning engineers, setting technical direction, reviewing code, and fostering an environment of continuous learning and growth.
  • Collaborate closely with data scientists to translate model requirements into efficient data pipelines, ensuring optimal data quality, processing, and integration.
  • Spearhead the implementation of best practices for model versioning, experiment tracking, and model evaluation to ensure reproducibility and transparency.
  • Drive the architecture and implementation of model deployment strategies, utilizing containerization (Docker) and orchestration (Kubernetes) for high availability and scalability.
  • Design and implement automated CI/CD pipelines for seamless model deployment, monitoring, and ongoing optimization.
  • Establish performance benchmarks and optimize models and infrastructure for maximum efficiency, scalability, and reliability.
  • Stay at the forefront of industry trends and emerging technologies, integrating the latest advancements into our ML ecosystem.

QUALIFICATIONS:

  • Requires 15+ years of related experience with a Bachelor's degree in Computer Science; or a Master's degree with an equivalent combination of education and experience.
  • Extensive experience architecting and building end-to-end machine learning infrastructure from model data preparation to model training to inferencing for complex and large-scale applications.
  • Proven leadership experience, with a track record of guiding and inspiring technical teams to deliver exceptional results.
  • Deep proficiency in machine learning frameworks such as TensorFlow, PyTorch, or equivalent, along with mastery of Python programming.
  • Strong expertise in containerization (Docker) and orchestration (Kubernetes) for deploying and managing machine learning applications.
  • Thorough understanding of software engineering principles, version control (Git), and collaborative development workflows.
  • Cloud platform experience (AWS, GCP, or Azure) and utilization of cloud-native services for ML infrastructure.
  • Prior experience with DevOps practices, continuous integration, and continuous deployment (CI/CD) pipelines.
  • Exceptional problem-solving aptitude and ability to resolve intricate technical challenges effectively.
  • Outstanding communication skills, with the ability to collaborate effectively across diverse teams and stakeholders.

If you are an exceptional Principal Machine Learning Engineer with a passion for crafting transformative ML infrastructure and deploying state-of-the-art models, we invite you to apply and become a vital part of our journey. Join us in redefining the boundaries of technology and [industry/domain] through the power of machine learning.

The US base salary range for this full-time position is $173,300 - $277,300

The base salary offer will be determined based on individual job-related factors such as the candidate’s experience, skills, and work location. 

Please note that the compensation range listed in this posting reflects only the base salary for this position and does not include other compensation elements or our comprehensive competitive benefits package. 

To learn more, visit our benefits page. Oportun Benefits

#LI-RR1 #LI-REMOTE

We are proud to be an Equal Opportunity Employer and consider all qualified applicants for employment opportunities without regard to race, age, color, religion, gender, national origin, disability, sexual orientation, veteran status or any other category protected by the laws or regulations in the locations where we operate.

 

California applicants can find a copy of Oportun's CCPA Notice here:  https://oportun.com/privacy/california-privacy-notice/.

 

We will never request personal identifiable information (bank, credit card, etc.) before you are hired. We do not charge you for pre-employment fees such as background checks, training, or equipment. If you think you have been a victim of fraud by someone posing as us, please report your experience to the FBI’s Internet Crime Complaint Center (IC3).

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