Machine Learning Engineer
Company: Disability Solutions
Location: New York
Posted on: October 21, 2024
Job Description:
ABOUT THE ROLEThe Personalization team at Peloton is looking for
a machine learning engineer to drive personalization and
recommendations for our highly engaged members across multiple
platforms. Their main focus will be to optimize the engagement and
discovery of Peloton content through research and application of AI
and ML techniques for content recommendations. They will work
closely with ML Engineers, Software Engineers, Product Managers and
Product Analysts to test ideas that drive member engagement. They
will have a unique opportunity to work with one of the most
granular data related to member engagement in the fitness industry.
We're looking for someone who's passionate about fitness and is
excited about the challenges of AI and machine learning to define
the future of connected fitness. YOUR DAILY IMPACT AT PELOTON
- Build and improve ML pipelines that power Peloton's content
recommendations.
- Research and apply best-in-class machine learning techniques
for recommender systems.
- Evaluate, implement, and improve machine learning models.
- Run A/B tests and experiments and analyze the results in
collaboration with our product analysts.
- Productionize, deploy and monitor machine learning models and
services.
- Collaborate and work closely with our platform teams to
leverage their tools and infrastructure to rapidly iterate on ideas
that drive delightful personalized experiences for millions of
users.YOU BRING TO PELOTON
- Degree in highly quantitative fields including Computer
Science, Machine Learning, Operational Research, Statistics,
Mathematics, etc.
- Experience/Interest working in at least one of following ML
disciplines: recommender systems, natural language processing or
computer vision.
- Strong understanding of software engineering principles and
fundamentals including data structures and algorithms.
- Experience writing code in Python, Java, Kotlin, Go, C/C++ with
documentation for reproducibility.
- Experience with relational and non-relational databases such as
Postgres, MySQL, Cassandra, or DynamoDB.
- Experience writing and speaking about technical concepts to
business, technical, and lay audiences and giving data-driven
presentations.PREFERRED QUALIFICATIONS
- MS/PhD in highly quantitative fields including Computer
Science, Machine Learning, Operational Research, Statistics,
Mathematics, etc.
- Comfortable working with near real-time ML applications.
- Proven track record of working with product managers to launch
ML-based product features.#LI-RF2#LI-HybridThe base salary range
represents the low and high end of the anticipated salary range for
this position based at our New York City headquarters. The actual
base salary offered for this position will depend on numerous
factors including individual performance, business objectives, and
if the location for the job changes. Our base salary is just one
component of Peloton's competitive total rewards strategy that also
includes annual equity awards and an Employee Stock Purchase Plan
as well as other region-specific health and welfare benefits.As an
organization, one of our top priorities is to maintain the health
and wellbeing for our employees and their family. To achieve this
goal, we offer robust and comprehensive benefits including:-
Medical, dental and vision insurance- Generous paid time off
policy- Short-term and long-term disability- Access to mental
health services- 401k, tuition reimbursement and student loan
paydown plans- Employee Stock Purchase Plan- Fertility and adoption
support and up to 18 weeks of paid parental leave - Child care and
family care discounts- Free access to Peloton Digital App and
apparel and product discounts- Commuter benefits and Citi Bike
Discount- Pet insurance and so much more!Base Salary
Range$127,300-$165,400 USDABOUT PELOTON:Peloton (NASDAQ: PTON),
provides Members with expert instruction, and world class content
to create impactful and entertaining workout experiences for
anyone, anywhere and at any stage in their fitness journey. At
home, outdoors, traveling, or at the gym, Peloton brings together
immersive classes, cutting-edge technology and hardware, and the
Peloton App with multiple tiers to personalize the Peloton
experience [with or without equipment]. Founded in 2012 and
headquartered in New York City, Peloton has millions of Members
across the US, UK, Canada, Germany, Australia, and Austria. For
more information, visit www.onepeloton.com.At Peloton, we motivate
the world to live better. "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. By combining hardware, software, content,
retail, apparel, manufacturing, Member support, and so much more,
we deliver an exhilarating fitness experience that unlocks our
members' greatness. Join our team to unlock yours.Peloton is an
equal opportunity employer and complies with all applicable
federal, state, and local fair employment practices laws. Equal
employment opportunity has been, and will continue to be, a
fundamental principle at Peloton, where all team members,
applicants, and other covered persons are considered on the basis
of their personal capabilities and qualifications without
discrimination because of race, color, religion, sex, age, national
origin, disability, pregnancy, genetic information, military or
veteran status, sexual orientation, gender identity or expression,
marital and civil partnership/union status, alienage or citizenship
status, creed, genetic predisposition or carrier status,
unemployment status, familial status, domestic violence, sexual
violence or stalking victim status, caregiver status, or any other
protected characteristic as established by applicable law. This
policy of equal employment opportunity applies to all practices and
procedures relating to recruitment and hiring, compensation,
benefits, termination, and all other terms and conditions of
employment. If you would like to request any accommodations from
application through to interview, please email:
applicantaccommodations@onepeloton.comPlease 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 on our careers page and all communications from the Peloton
recruiting team and/or hiring managers will be from an @ 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.
Keywords: Disability Solutions, Philadelphia , Machine Learning Engineer, Engineering , New York, Pennsylvania
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