Hi, We’re AppFolio.
We’re innovators, changemakers, and collaborators. We’re more than just a software company — we’re a cloud-based SaaS company that creates products to make our customers’ lives easier. We’re revolutionizing the way people do business, and we want your ideas, your enthusiasm, and your passion to help us keep on innovating.
We love where we work, and you can, too.
Who we are looking for:
We are hiring a Sr. Machine Learning Software Engineer to contribute to our rapid product development pace. Our Engineers work collaboratively to set the technical direction for our SaaS products, developing easy-to-use solutions for our customers.
We are looking for machine learning engineers to help us bring next-generation products to market. The ideal candidate will be a curious, rigorous, team-player passionate about bringing real AI products to life. The ideal candidate will also be versatile and able to apply a wide variety of technical skills to solve problems.
This opening is on our AppFolio Property Manager product development team, working closely with our CTO.
- Work with our product development teams to design and develop machine learning and deep learning systems to build customer-facing products and features.
- Find and analyze customers’ problems that could be solved with machine learning, define the data needed to implement the models, and specify the metrics to measure models’ performance.
- Work closely with, and incorporate feedback from other engineering team members, QA, product owners, and our customers.
- Leverage both AppFolio’s structured and unstructured datasets to build new features and products that customers love
- Exploring and visualizing complex data sets in order to gain insights.
- Analyzing multiple ML algorithms that could be used to solve a given problem, use your seasoned intuition to rank their likelihood of success, and define the right set of metrics to track model performance.
- Leverage agile practices and encourage collaboration, prioritization, and urgency to develop rapidly.
- Train models, tune their hyperparameters, and track datasets and experiment results.
- Implementing preprocessing and feature engineering with and without big data platforms.
- Deploy models to production in cloud environments like AWS or Google Cloud.
- Implement relevant industrial programming and deployment techniques such as unit tests, continuous integration, and good monitoring
- Research, share, and recommend new technologies and trends
You know you’re the right fit if…
- You’re experienced with all parts of the model-building ecosystem: You can go from raw, dirty data to a well-performing model that runs on demand in production.
- You have hands-on experience developing real products enabled by machine learning technology, preferably in a SaaS environment.
- You love learning about new technologies but love building real products more.
- You have a high degree of initiative, creativity, persistence, and a strong focus on producing tangible results.
- You have the ability to take academic or commercial models and concepts (including from other fields) and translate them into working code to solve problems.
- You have hands-on experience with at least one Deep Learning framework (PyTorch, TensorFlow, etc.).
- You have hands-on experience with transformer architectures in the Natural Language Processing and Computer Vision domains.
- You have hands-on experience with at least one Cloud Infrastructure Provider (AWS, Google Cloud, etc).
- You are comfortable working in a Linux command line and have programming skills in Python, Java, or closely related object-oriented language.
- You are comfortable writing vectorized code such as Matlab, Python, etc.
- You care about work-life balance and want your company to care about it, too; you'll put in the extra hour when needed but won't let it become a habit.
Additional Skills and Knowledge:
- Programming skills in Python or similar object-oriented language
- Experience using NumPy, SciPy, Pandas, and Scikit-learn
- Experience using PyTorch and PyTorch Lightning
- Experience using Apache Spark
- Experience using SQL, Git, Linux, and Docker.
- Bachelors in Statistics, Computer Science, Data Science, or other quantitative fields.
- Applied Machine Learning fundamentals such as decision trees, neural networks, statistical modeling, and/or clustering
- Experience using OpenAI API for LLM like GPT 3.5 and GPT 4.
Nice to Have:
- Ph.D. or Masters in Statistics, Computer Science, Data Science, or other quantitative fields.
- Experience working across all levels of the development stack
- Publicly verifiable work on Github or in Kaggle competitions
If you are interested in creating exceptional SaaS products, and contributing to a successful company, apply today!
Compensation & Benefits
The base salary that we reasonably expect to pay for this role is: $135,000-$190,000
The actual base salary for this role will be determined by a variety of factors, including but not limited to: the candidate’s skills, education, experience, etc.
Please note that base pay is one important aspect of a compelling Total Rewards package. The base pay range indicated here does not include any additional benefits or bonuses/commissions that you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits including but not limited to:
- Paid Time Off (PTO)
- Medical, dental, and vision benefits
- Long-term and short-term disability insurance
- Wellness benefits
Interns / full-time temporary / eligible variable hour employees are eligible for benefits including but not limited to:
- Wellness benefits
AppFolio (NASDAQ: APPF) was founded in 2006 with the mission to revolutionize vertical industry businesses by providing great software and service. Our easy-to-use, cloud-based software helps our customers more effectively market, manage, and grow their businesses.
To find out more about what AppFolio has to offer, check out appfolioinc.com/careers.