Engineering Manager, AI/Ml
USA
Applications have closed
Peloton
Access high-energy workouts, instantly. Discover Peloton: streaming fitness classes to you live and on-demand.The Artificial Intelligence team at Peloton is looking for an experienced Engineering Manager, to help staff and lead a team of engineers responsible for ideating and scaling a quality assurance and data infrastructure for multi-platform, global, and rapidly growing products. You will work with Peloton’s AI Data Infrastructure organization to help deliver on our vision to build a world-class infrastructure with a focus on scalability, privacy, and security.
The manager will focus on making sure the team is resourced appropriately, drive day-to-day delivery and prioritization of work, and lead, coach and mentor developers. They’ll support the AI/ML teams (personalization, computer vision, wearables, and voice) in ensuring delivery and alignment with company initiatives.
Responsibilities
Team
- Evolve AI Data Infrastructure product and technical roadmap and drive for its execution.
- Manage and grow a team of machine learning infrastructure engineers, software engineers, and data engineers responsible for delivering to that roadmap.
- Establish processes to effectively improve machine learning engineering and operational excellence.
- Identify and drive the adoption of new technologies, architecture and skill sets for the team to take on new challenges.
- Partner closely with Machine Learning Engineers, Data Platform teams, and AWS.
- Partner closely with Recruiting to identify and hire strong candidates from diverse backgrounds.
Growing People
- Motivate and drive a continuous performance-based culture within the team. Provide adequate management support for the team in the form of team meetings, 1:1’s and other forums as needed to support the group and individual development objectives of team members.
- Coach and mentor team members. Foster their career growth through setting objectives, regular feedback, and sharing best practices.
- Lead by example to actively maintain and build a culture of learning, respect, transparency, and trust.
Project Leadership
- Collaborate within the AI and ML teams to identify data/infrastructure needs that support project goals.
- Scale up and build the next generation of its AI infrastructure, specifically its core compute and data platform
- Handle planning and breaking down large projects; Manage program and project risks appropriately; Jira and scrum ceremonies; Identify and mitigate internal and cross-functional dependencies and blockers.
- Lead with a “members first” mentality, and how individual projects enrich the overall experience for end users.
Technical Leadership
- Drive technical decision making through objectively assessing trade offs based on architecture, scope, business priorities, and impact to product experience.
- Leverage a strong technical foundation and experience to provide appropriate guidance in a team of senior and staff machine learning engineers and software engineers.
- Work with engineers to support and nurture the team codebase to leverage software best practices (e.g. SOLID, OOP principles, code coverage, CI/CD/Cx)
Qualifications
- BS/MS or PHD in Computer Science or a related quantitative field with a focus on statistics, machine learning and mathematics. Strong background in software engineering.
- 5+ years of technical management experience.
- 5+ years of combined machine learning and software development experience. Demonstrable experience building and deploying machine learning systems in production.
- Technical understanding of different components of a modern big data infrastructure is a must-have, such as Spark, Kafka, Kubernetes, Sagemaker, Hadoop ecosystem, and etc.
- Experience scaling data infrastructure products and tools used by engineering teams.
- Experience deploying machine learning models and algorithm pipelines on low-power edge devices with compute constraints.
- Experience working with Agile methodology and delivery of quality software as part of an Agile team.
- Demonstrable experience shipping several large projects with multiple dependencies across teams
- Ability to mediate between competing product and technical priorities; align priorities and goals through collaboration with technical leads and product managers.
- Experience with coaching and mentoring engineers at different stages in their career, including senior and staff level engineers. Able to demonstrate the ability to identify the strength and weaknesses of individuals in order to maximize team effectiveness.
- Experience hiring talented engineers at different levels.
Please note: This is a full-time position that will be remote initially (due to COVID-19) and based in will be based in our New York City HQ once safe to re-open the office.
ABOUT PELOTON:
Peloton uses technology + design to connect the world through fitness, empowering people to be the best version of themselves anywhere, anytime. We have reinvented the fitness industry by developing a first-of-its-kind subscription platform. Seamlessly combining hardware, software, and streaming technology, we create digital fitness and wellness content and products that Members love. In 2020 Peloton committed to becoming an antiracist organization with the launch of the Peloton Pledge. Learn more, here.
“Together We Go Far” means that we are greater than the sum of our parts, stronger collectively when each one of us is at our best. In order to be the best version of Peloton, we are deeply committed to building a diverse workforce and inclusive culture where all of our team members can be the best version of themselves. This work has no endpoint; it is the constant work of running an organization that strives to reach its full potential. As a first step in our commitment, we announced the Peloton Pledge to invest $100 million over the next four years to fight racial injustice and inequity in our world, and to promote health and wellbeing for all, from the inside out.Peloton is an equal opportunity employer and committed to creating an inclusive environment for all of our applicants. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. If you would like to request any accommodations from application through to interview, please email: applicantaccommodations@onepeloton.com
Please be aware that fictitious job openings, consulting engagements, solicitations, or employment offers may be circulated on the Internet in an attempt to obtain privileged information, or to induce you to pay a fee for services related to recruitment or training. Peloton does NOT charge any application, processing, or training fee at any stage of the recruitment or hiring process. All genuine job openings will be posted here on our careers page and all communications from the Peloton recruiting team and/or hiring managers will be from an @onepeloton.com email address.
If you have any doubts about the authenticity of an email, letter or telephone communication purportedly from, for, or on behalf of Peloton, please email applicantaccommodations@onepeloton.com before taking any further action in relation to the correspondence.
Peloton does not accept unsolicited agency resumes. Agencies should not forward resumes to our jobs alias, Peloton employees or any other organization location. Peloton is not responsible for any agency fees related to unsolicited resumes.
Tags: Agile AWS Big Data CI/CD Computer Science Computer Vision Consulting CX Engineering Hadoop Jira Kafka Kubernetes Machine Learning Mathematics ML models OOP PhD Pipelines SageMaker Scrum Security Spark Statistics Streaming
Perks/benefits: Career development Health care Transparency Wellness
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