At Weights & Biases, our mission is to build the best developer tools for machine learning. Weights & Biases is a series C company with $200 million in funding and a rapidly growing user base. Our platform is an essential piece of the daily work for machine learning engineers, from academic research institutions like FAIR and UC Berkeley to massive enterprise teams including iRobot, OpenAI, Toyota Research Institute, Samsung, NVIDIA, Salesforce, Blue Cross Blue Shield, Lyft, and more.
Reporting to the Head of Data Science, the Machine Learning Engineer (MLE) will own the interface between our Data Science Team and our Data Platform Team, while making the results of Data Science into ML Applications for the business. In particular, the MLE will work directly with scientists to refine their models, and then utilize Weights and Biases’ products to instrument and actualize production services. These services will be oriented to core business objectives.
The MLE will partner closely with Data Science and Data Engineering on the same team. Additionally, the MLE will partner with Product to understand applications of ML to improve our offerings, with our Go-To-Market team to build services to equip them with sales-critical data resources, with Engineering to introduce new ML-backed features into our product, with Growth to optimize our interface with the broader ML world, and finally with the rest of the company to demonstrate how Machine Learning can drive the business forward.
What you’ll acheive
- You’ll research, build and deploy Machine Learning Models and Services equipped with W&B integrations.
- Think critically about W&B APIs and collaborate with the Engineering Team to build feature improvements for ML Practitioners using the W&B platform.
- Collaborate with Data Scientists to transform business problems into services and ML products that will be used by customers.
- Collaborate with the Data Platform team to establish patterns and infrastructure to make it easy for other technical employees to train and deploy ML models.
- Immediately your focus will be on deploying and tuning an internal recommendation system, and a lead scoring model.
What we’re looking for
- Excited about MLOps, and have a lot of knowledge about Machine Learning System Design. This role is a bit meta, because you’ll be doing MLOps at an MLOps company, so we want you to be really excited about partnership with our Product and Engineering teams to use your work to guide the product direction.
- Very familiar with Machine Learning models; we expect that you’re already very familiar with when and where ML models can impact a business.
- Strong engineering skills; both an understanding of coding for ML and an understanding of how core engineering systems work will be important for this role.
- Excellent communicators; the ability to understand partner’s needs, and in turn represent highly technical concepts to a variety of business partners is essential for success.
- 🏝️ Flexible Time Off
- 🩺 100% Medical, Dental, and Vision for employees and Family Coverage
- 🏠 Remote first culture with in office flexibility in San Francisco
- 💵 $500 home office budget with new high-powered laptop
- 🥇 Truly competitive salary and equity
- 🚼 12 weeks of Parental leave (U.S.)
- 📈 401(k) (U.S.)
We encourage you to apply even if your experience doesn’t perfectly align with the job description as we seek out diverse and creative perspectives. Team members who love to learn and collaborate in an inclusive environment will flourish with us. We are an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need additional accommodations to feel comfortable during your interview process, reach out at email@example.com.