Software Engineering, Data Science
San Francisco, CA, USA
Posted on Friday, August 11, 2023
At MainStreet, we’re problem solvers.
Our products aim to do one thing: save startup founders and small business owners time, money, and peace of mind. We started by demystifying complicated tax credits, saving over $100M – and countless hours of tax code research 🥱– for founders in nearly every industry. Since our sort-of viral beginnings in 2019, we’ve raised a $60M Series A, expanded our product lines (with more in the works), and grew from 3 employees to our current team!
We owe our success to the strength of our team. Before joining MainStreet, we helped build companies like Intuit, PayPal, Google, Apple, Coinbase, Gusto, LinkedIn, Slack, and more. We’re fellow founders, engineers, accountants, designers, dog (and cat) lovers, adventurers, coders, and parents. We move fast. We think big. We don’t take ourselves too seriously. And we’d love for you to join us.
MainStreet is looking for a Machine Learning Engineer who will play a pivotal role in designing, developing, and implementing machine learning models and algorithms that power our groundbreaking product. You will work closely with a team of talented engineers and data scientists to create intelligent systems that solve complex problems and unlock new possibilities that lead to dollars earned for our customers.
What you’ll do
- Research and Development: Conduct research to explore state-of-the-art machine learning algorithms, stay updated on the latest advancements, and propose innovative solutions to tackle business challenges effectively
- Model Development: Design, build, and optimize machine learning models and algorithms that can be deployed on various platforms and integrated into our products
- Data Preprocessing: Prepare and clean datasets to ensure they are suitable for model training and validation, while addressing issues such as missing data and outliers
- Model Training and Evaluation: Train machine learning models using vast datasets, validate their performance, and fine-tune hyperparameters to achieve optimal accuracy and generalization
- Integration and Deployment: Collaborate with software engineering teams to integrate machine learning models into production systems and ensure seamless deployment in real-world environments
- Performance Monitoring: Implement monitoring and logging mechanisms to track model performance in production and detect potential anomalies or degradation in accuracy
- Continual Improvement: Conduct thorough analysis of model performance, identify areas for improvement, and iterate on existing models to enhance their effectiveness
- Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to define project requirements and ensure alignment with business objectives
- Documentation: Create clear and comprehensive documentation for models, algorithms, and implementation processes, enabling easy knowledge transfer within the team
- Innovation and Research Contribution: Stay up-to-date with the latest trends and advancements in machine learning, participate in research discussions, and contribute to the company's intellectual property through patent filings and publications
What we’re looking for
- Education: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. A Ph.D. is a plus
- Experience: Demonstrable experience in developing and deploying machine learning models in real-world applications. (7 years of experience, depending on the seniority level)
- Programming Skills: Proficiency in programming languages like Python, R, or similar, along with experience in using machine learning libraries such as TensorFlow, PyTorch, or scikit-learn
- Mathematics and Statistics: Strong understanding of linear algebra, calculus, probability, and statistics, coupled with the ability to apply these principles to machine learning problems
- Deep Learning: Familiarity with deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models
- Data Handling: Experience with data preprocessing, feature engineering, and data augmentation techniques to enhance model performance
- Software Engineering: Understanding of software engineering principles, version control, and the ability to write clean, modular, and maintainable code
- Problem-Solving: Analytical mindset with a proven ability to break down complex problems, develop innovative solutions, and troubleshoot issues effectively
- Communication: Strong verbal and written communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders
- Team Player: A collaborative approach to work, with a willingness to contribute to team success and a commitment to promoting a positive work environment
- Base salary range for this position is $135,000 - $235,000 and is based upon years of experience that is commensurate with the level of the position
- Robust equity program with significant upside potential
- Benefits including medical, dental, vision, disability, life, and 401k
MainStreet takes a holistic approach to small business management so you can grow smarter, not harder. We plug into your accounting and payroll systems to check for savings opportunities in unlikely places. From complex government tax credits to exclusive discounts on the tools you use every day, we save you thousands of dollars, hundreds of hours, and countless headaches.
Throughout the year, you’ll track expenses and savings through your MainStreet dashboard and tag us in on big purchases and contract negotiations. Come tax season, we’ll do the paperwork and even let your CPA take all the credit. Consider us your silent partner-in-savings, your financial secret weapon, your smart (not a) bank – whatever you want to call us. We’ve got your back so you can get back to building your business. ✨
Our $60M Series A
We’ve raised over $60M from an incredible community of partners, operators, and founders, including SignalFire (who led our Series A), Ryan Hoover (Product Hunt founder), Ashton Kutcher’s Sound Ventures, Des Traynor (Intercom co-founder), Gradient Ventures (a Google Venture Fund), Ron Conway’s fund SV Angel, Shrug Capital, and Tusk Ventures.
How we think about diversity
We try to make sure the diversity of our customers is reflected in the team that serves them. Because when we include people of all races, genders, sexual orientations, ages, and identities — we end up building a better experience for everyone who uses MainStreet.
We know we need to be intentional in our hiring practices in order to overcome systemic biases we may be blind to. So, if your lived experience has given you a unique perspective on business, startups, or any other aspect of our business – even if you don’t meet all the requirements – please still apply and let us know so we can make sure your application gets the attention it deserves.