Manager, Machine Learning (EM1, Sr EM) - Discovery
Twitter is what’s happening and what people are talking about right now. For us, life's not about a job, it's about purpose. We believe real change starts with a conversation. Here, your voice matters. Come as you are and together we'll do what's right (not what's easy) to serve the public conversation.
Who We are: Discovery is committed to building geographically distributed teams and we welcome applicants across the US/Canada to apply.
Twitter's Discovery teams are dedicated to getting the majority of the world to converse in public using Twitter. We are composed of many teams across the company, including Product, Engineering, Design, and Research. These teams are responsible for understanding the needs of all users including new users and users who are not very active, and help them discover the value of Twitter by building personalized products.
We are hiring multiple ML Engineering Managers across various levels (EM1 and Sr EM). These include teams for Acquisition, Activation, and Re-engagement.
The mission is to instantly connect people with conversations and audiences most meaningful to them! We realize this goal involves work in areas such as machine learning, applied data science, recommendation systems, and information retrieval systems. Do you want to make a huge impact while working with large data sets at scale? If so, a Discovery team is a good fit for you!
What You'll do: You will lead a world-class team of Machine Learning and Software engineers. We're looking for a hands-on, technical manager with a passion for working on customer-facing relevance products. The ideal candidate would be equally comfortable guiding the modeling team's long-term roadmap and working with the product engineering team to identify new product relevance problems.
As a Manager you will:
- Ensure the team fully understands the goals and objectives of Twitter as a company and how they fit in it.
- Mentor the professional development of each direct report through personal and performance management.
- Work with your Product, Data Science, and EM partners to understand and incorporate customer problems into the team's roadmap, propose ML-based solutions to customer needs and align priorities with our overall product strategy.
- Work with your Tech lead, take responsibility for the group's technical strategy and roadmap – create and track success metrics, and evaluate models' performance and understand levers of model performance.
- Seek diverse perspectives to drive bottom-up innovation and create consensus from all technical partners inside and outside the team ( applied research teams).
- Be an engineering talent magnet to make the team successful in its established mission.
Who You Are
- You have experience improving the quality of consumer products with A/B experimentation best practices and defining key metrics.
- You have a background in machine learning, including experience with deep learning, prediction/binary classification, and decision trees. Experience with recommender systems and cold-start problems, in particular, is a plus.
- You have experience leading teams that have done modeling in cloud infrastructure like GCP, AWS, etc.
- You can hold your own technically with engineers on the team and give constructive feedback on projects and ideas.
- You have a sense of urgency, move quickly, and ship things.
- You support giving engineers the tools, confidence, and motivation they need to make decisions independently, leading to your engineers' recognition.
- You are a strong recruiter of engineering talent and comfortable closing applicants for your team and the business.
- 6+ years of related experience
- Bachelor's degree or equivalent experience in computer science, engineering, or other related areas (MS/PhD is a plus)
- Previously tech-led or managed a team of 5 or more engineers building relevance based consumer products, ML models and systems in a production setting
- Knowledge of and experience with techniques used in data mining, machine learning, information retrieval, or recommendation systems.
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.