Machine Learning Engineer
We started with just one home and an idea: to bring homeowners and renters together with smart technology and caring local teams. Today, we’re the largest full-service vacation rental company in North America thanks to the people who give us their best every day. You’ll fit right in here if you’re curious, entrepreneurial, and thrive in a rapid-growth environment.
Why Engineering at Vacasa
We build the tools that allow other departments to succeed. We’re constantly experimenting and fine-tuning our products. We value stability, security, and scalability. Our favorite word is autonomy—we want everyone to have a voice.
What we’re looking for
As a Machine Learning Engineer at Vacasa, you will join a nimble, cross-functional team of bright machine learning engineers and data scientists. This team has a high impact on company revenue and operational efficiency. You will productionize ML models in the cloud using Python, and adapt feature engineering techniques to both batch and real-time pipelines. This includes writing robust, maintainable, and reliable systems with validation, monitoring, metrics, for both internal and external customers. You will be expected to collaborate on initiatives, and be coached by more senior engineers. You will seek out solutions from both internal team members and external sources when you hit roadblocks, and begin diving in on projects independently.
Vacasa’s machine learning and data science research is broad. We train dozens of models, from dynamic daily pricing for all units, to probability models that are used throughout the company. There’s potential to explore and implement recommender systems, NLP techniques, and neural networks. Vacasa has hundreds of millions of records for model training. Help us discover value in our data and bring it to customers!
What you'll do
- Productionizes machine learning models using AWS, Python 3, CI/CD, and Terraform.
- Writes maintainable, reliable, and robust pipelines complete with unit and integration tests.
- Contributes to all phases of development and delivery, including a weekly on-call rotation.
- Develops dashboards to monitor pipeline health, and alert on key metrics.
- Collaborates with a cross-functional team of engineers, QA, data scientists, and Product.
- Continually update your engineering skills using modern tools and techniques.
- Delivers results to stakeholders on time and within budget.
- Participates in code reviews, peer design, and demonstrates respectful, effective communication.
- Balances best engineering practices with business needs.
Skills you'll need
- 3+ years of software engineering, including 2+ years of machine learning engineering or equivalent experience and/or education.
- Familiarity with machine learning algorithms, including supervised and unsupervised.
- Ability to function in a “big data” environment such as Apache Spark.
- Familiarity with the AWS ecosystem and tools such as S3, Glue, or SageMaker.
- Strong Python experience.
- RDBMS and ETL experience, data warehouse experience is a plus.
- Experience writing infrastructure as code, Terraform is a plus.
- Ability to work in office 4 days / week with the option to work from home 1 day / week
- The benefit of a hybrid schedule requires a reliable internet connection and must meet a minimum of 50 mbps
What you’ll get
- Competitive salary
- Ability to participate in our Employee Stock Purchase Plan
- Paid vacation and holidays
- Meal vouchers
- Career advancement opportunities
- Employee discounts
- All the equipment you’ll need to be successful
- Great colleagues and culture
Vacasa is an equal opportunity employer committed to fostering a diverse and inclusive workplace. We do not discriminate against applicants based upon race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, or other classes protected by applicable law. Veterans are encouraged.
Vacasa is committed to maintaining a safe and productive work environment. Possession, use, or being under the influence of alcohol or illegal drugs in the workplace is prohibited.
An offer of employment for this role will be contingent upon the successful completion of a background check and/or OFAC screening.