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Who we are: Discovery is committed to building geographically distributed teams and we welcome applicants across the US/Canada to apply.

Twitter is looking for an engineering leader to oversee the relevance team in Customer Journey Org. The Customer Journey Org's mission is to reach every person in the world wherever they are, show them the value of Twitter, and get them to use Twitter regularly. The relevance team aims to help personalize product experiences owned by Customer Journey Org, like graph building, logged-out experiences, email recommendations, etc. We solve product problems by building recommendation systems, developing cohort-based user models, and partnering with ML teams across the company. Customer Journey is a high-impact team with a large product scope and the ability to influence billions of users who are yet to use Twitter. It has a vital role in attracting and retaining new and light users on the platform, contributing significantly to audience growth for Twitter.

What You'll do: You will join the Customer Journey team and lead a world-class team of Machine Learning 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 for the Customer Journey Relevance team, you will: 

• Be responsible for a large-scale production machine learning pipeline consisting of offline workflows and online services.
• Mentor the professional development of each direct report through personal and performance management.
• 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.
• 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. 
• Seek diverse perspectives to drive bottom-up innovation and create consensus from all technical partners inside and outside the team ( applied research teams).
• Ensure the team fully understands the goals and objectives of Twitter as a company and how they fit in it. 

Who You Are

• 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 improving the quality of consumer products with A/B experimentation best practices and defining key metrics.
• 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.

Requirements

• BA/BS or higher in Computer Science (or related field)
• Previously tech-led or managed a team of 5 or more engineers building ML models and systems in a production setting
• Knowledge of and experience with techniques used in data mining, machine learning, information retrieval, recommendation systems, or natural language processing.

We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.

San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.