Software Engineer, Machine Learning (Senior/Staff/Principal)

Monarch is a powerful, all-in-one personal finance platform designed to help make the complexity of finances feel simple again. Since launching in 2021, we’ve become the top-recommended personal finance app by users and experts. Our goal? To take the stress out of finances so our members can focus on what truly matters.

We are a team of do-ers led by experienced entrepreneurs who are passionate about helping our members reach their financial goals. We are hyper focused on building a product people love and continuing to evolve based on user feedback.

As a fully remote company (even before COVID!), we welcome applicants from almost anywhere. Our team collaborates synchronously mostly from 9 AM – 2 PM PT and embraces asynchronous work to stay connected across time zones.

Join us on our mission to transform lives by simplifying money, together.

Monarch Money is seeking an experienced Software Engineer with a focus on Machine Learning. We are big believers in using the power of ML/AI (and in particular, GenAI) to help people process and understand their finances, as well as make plans for and automate future improvements to their financial lives.

As one of Monarch Money's first ML engineers, you will play a key role in shaping how we integrate machine learning into our existing and future product features. Beyond technical execution, you will be a strategic thought partner, contributing to the growth of our product, company, and culture. With significant autonomy, you will own end-to-end implementation while keeping the team informed of the latest advancements in the field.

In this role, you will help shape the roadmap for ML at Monarch Money, working on impactful initiatives from day one. Early projects may include enhancing transaction enrichment using GenAI to achieve best-in-class accuracy, advancing our "Monarch Assistant" conversational agent, and building in-product recommendations to help users navigate their finances effortlessly. Additionally, you will explore ways to leverage ML to enhance the relationship between users and financial professionals, making financial planning more efficient and personalized.

• Help propose, gather and prioritize ideas on how we can harness ML to pursue Monarch's mission of improving household's personal financial lives.

• Rapidly prototype and experiment with early ideas to assess feasibility and impact.

• Train, evaluate, and tune ML models.

• Work with the Product Engineering and Data teams to gather and preprocess the appropriate datasets.

• Deploy ML models to production.

• Help build ML infra and tooling where appropriate.

Not all of the below are strict requirements—interest/passion/intellect can often be more valuable than experience. That said, we'd love to see:

• Experience with GenAI, including using techniques like Retrieval Augmented Generation (RAG) and Agentic models, as well as evaluation techniques for GenAI models.

• Experience with "classic" ML models (pre-GenAI), in particular ones focused on Natural Language Processing (NLP)—everything from TF-IDF and SVMs to BERT and Word2Vec. Be comfortable with generating/using embeddings.

• Great collaboration/communication skills and a sharp product sense.

• Comfort working with large-scale data, especially sensitive.

#LI-DNI

• Work wherever you want! As a fully remote company with no central office, we want you to work wherever you are happiest and most productive. Whether that’s out of your home, a co-working space, or elsewhere.

• Competitive cash and equity compensation in a hyper growth, early stage company 🚀.

• Stipend to set-up your ideal working environment.

• Competitive Benefit Plans for employees based on your location (e.g. in the US we offer: Medical, dental and vision benefits and the ability to contribute to a 401k plan).

• Unlimited PTO.

• 3 day weekend every month! We take off the “First Friday” every month to focus on rest, recuperation, or just having fun!

We are an equal opportunity employer and value diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.