About the position
Etsy is looking for a Machine Learning Engineer to join our Growth team. This team focuses on improving the buyer experience and increasing the number of visits that turn into purchases (aka driving conversion!). You'll help us build systems and tools that personalize the shopping journey, ensuring buyers find relevant information at the right time, ultimately helping them discover the perfect handmade or vintage item. We're building a new machine learning team to support our product engineering squads, where you'll play a key role in shaping how we understand our buyers and tailor their experiences. You'll work hands-on with a cross-disciplinary team to deliver robust, scalable production models and tools that will be A/B tested live on Etsy. Staying at the forefront of ML research, you'll bring its best ideas to life for millions of Etsy shoppers. This is a full-time position reporting to the Senior Engineering Manager, Growth. In addition to salary, you will also be eligible for an equity package, an annual performance bonus, and our competitive benefits that support you and your family as part of your total rewards package at Etsy.
Responsibilities
- Collaborate in a cross-functional team to prioritize and execute projects that align with our product goals.
- Leverage experimentation and data: Use insights from previous experiments and research to ideate and implement efficient ML solutions.
- Partner closely with ML engineers, full-stack engineers, applied scientists, and product managers to develop and test large-scale experiments.
- Optimize ML models to meet latency SLAs at Etsy's scale and launch live A/B tests to validate hypotheses.
- Build, deploy, test, and maintain scalable ML models by applying cutting-edge research and industry practices.
Requirements
- Experience developing impactful solutions to machine learning & NLP problems involving data extraction, developing and training machine learning models, and working the new model into production applications.
- Experience building scalable solutions taking into account localization specific needs to cater to global customer needs.
- Strong engineering and coding skills, with the ability to write high quality production code. Proficiency in Python, Scala, Java, PHP and/or other equivalent languages.
- Experience working with machine learning frameworks such as scikit-learn, PyTorch, TensorFlow/TFX and data engineering tools like Spark, Kubeflow or Airflow.
- Continuous and recent experience of pushing production level Machine Learning code.
- Product-minded and passionate about leveraging ML to enhance user experiences.
- Analytical thinker and understand how to wield data to make informed decisions about your work.
- An M.S. in Computer Science or related engineering fields, or 3+ years of practical machine learning experience.
Benefits
- Equity package
- Annual performance bonus
- Competitive benefits that support you and your family
