Senior Software Engineer, Machine Learning

About Kikoff:

Kikoff is the fastest consumer fintech to hit $100MM ARR and is reinventing the credit space, offering credit-building solutions that are affordable, accessible, and educational to address the catch 22 on improving credit. Our core product, the Kikoff Credit Account, has helped over 1 million customers build better credit. Kikoff has been featured by Nerdwallet, Forbes, Buzzfeed, Business Insider, CNBC, and others; and our app has a 4.9 rating amongst thousands of reviews. But Kikoff is more than just a credit builder: we are a long-term financial partner for our customers, and we have an exciting product roadmap of solutions to help our customers reach their financial goals.

Why Kikoff:

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We are backed by some of Silicon Valley’s top VCs. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact.

We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash advance underwriting model and other machine learning use cases. The ideal candidate will have a strong background in software development, machine learning, and data engineering, with experience in deploying scalable ML models in production environments.

Key Responsibilities:

• ML Infrastructure and Operations: Design, build and maintain the infrastructure required for optimal extraction, transformation, and loading of data from various sources. Develop and manage data pipelines and workflows for machine learning models.

• Model Development and Deployment: Design, develop, and implement machine learning models for underwriting and other financial service applications. Ensure models are robust, scalable, and maintainable.

• Collaboration: Work closely with data scientists, software engineers, and product managers to integrate machine learning models into production systems. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

• Performance Monitoring: Monitor and evaluate the performance of deployed models, ensuring they meet the desired accuracy and efficiency metrics. Implement processes for continuous improvement and optimization of models.

• A/B Testing and Experimentation: Design and implement experiments to optimize models and ensure they align with business goals.

• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of learning and growth within the team.

Qualifications:

• Educational Background: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree preferred.

• Experience: Minimum of 3 years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments.

• Technical Skills:

  • Proficiency in programming languages such as Python or Ruby.

  • Strong understanding of data structures, algorithms, and software design principles.

  • Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).

  • Familiarity with MLOps practices and tools for continuous integration and deployment of ML models.

  • Experience with cloud services (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes).

• Analytical Skills: Strong problem-solving skills with the ability to analyze complex data sets, apply advanced data science techniques, and derive actionable insights. Proficient in building predictive models, performing statistical analysis, and utilizing machine learning algorithms to identify trends, patterns, and opportunities for optimization.

• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

What we’re like:

- Scrappy. We had a product goal and put out the MVP, collecting our first users with steady growth via paid channels in four months. We don’t cut corners when we know we’ll need them but we don’t build things without that need. We don’t like inefficiency but we dislike operationalizing one-off tasks even more.

- Risk-oriented. Everything has risk, but a mature team knows how to make these tradeoffs. That’s why we built the MVP fast––because time is your most valuable asset and is practically fungible with money in the startup world.

- Data-obsessed. We all look at data and pull it, and we believe that understanding the mechanics can yield valuable insights. Complex systems require elegant, not just simple solutions. You absolutely need to be interested in data if you want to leverage your knowledge of systems.

- Lucky. That’s how we look at this journey so far. From our timing of fundraising, to the circumstances in which we came together, to the initial product traction we’re getting, there’s no other word to describe it. We are grateful you are reading this, and we know that if you’re meant to be with us on this journey, then we will see you soon.

About Kikoff:

Kikoff is a personal finance platform designed to help millions of underserved Americans achieve financial wellness. Our mission is to provide refreshingly fair, effective, and simple pathways for everyday people to meet their financial goals. We design financial products that simplify credit building so our users can reach their financial goals. Kikoff is a Series B company and has raised over $42 million in total funding. Investors include Portage Ventures, Lightspeed Venture Partners, GGV, Coatue, Core Innovation Capital, and basketball star Stephen Curry. Kikoff was founded in 2019 and is headquartered in San Francisco with an office in Reno.

Why Kikoff:

This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We are backed by some of Silicon Valley’s top VCs. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact.

🏥 Medical, dental, and vision coverage - Kikoff covers the full cost of health insurance for the employee!

📈 Stock Options

🏝 Generous unlimited vacation policy to help you recharge

💰 US salary range for this full-time position consists of base + equity + benefits

Visa sponsorship available: Kikoff is willing to provide sponsorship for H1-B visas and U.S. green cards for exceptional talent.

Equal Employment Opportunity Statement:

Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Please reference the following information for more information:https://www.eeoc.gov/sites/default/files/migrated_files/employers/poster_screen_reader_optimized.pdfhttps://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf 

If you need reasonable accommodation for a job opening please connect with us at [email protected] and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process.

San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, Kikoff will consider for employment qualified applicants with arrest and conviction records.

Compensation Range: $349K - $558K

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