STAFF MACHINE LEARNING ENGINEER
Descripción de la oferta de empleo
Through our intelligent skills platform and a global community of instructors, we’ve helped over 70 million learners and organizations achieve their goals.
Come join us in ensuring everyone, everywhere has access to the skills they need to unlock their potential and create possibilities for themselves and others.
Hybrid work Udemy is headquartered in San Francisco with global offices in Australia, India, Ireland, Türkiye, and other US locations.
Our robust hybrid work model spans San Francisco, Denver, Ankara, Dublin, Mexico City and Melbourne.
This hybrid position requires two days per week in the office at the nearest hub.
__________________________________________________________________________________________________ About you You’re an analytical problem-solver ready to put your skills toward purposeful work that has a global impact.
You want to lead the way in innovation, exploring the latest technologies and finding new solutions.
You thrive in a collaborative environment and are eager to work with and learn alongside the best in Product, Design, and Engineering.
About this role Udemy is looking for a machine learning engineer to join a team largely focused on exploring and building novel applications of generative AI to improve the teaching and learning experience.
In this role, you will build products that leverage deep learning and large language models (e.
., GPT).
You will work as part of a cross-functional agile team that includes data scientists, machine learning engineers, software engineers, designers, and product managers.
Are you passionate about learning, willing to take technical challenges, care about making an impact, and looking for a diverse, collaborative, and fun environment that also values quality? If so, come help us improve lives through learning at Udemy! What you'll be doing Own machine learning and deep learning systems, platforms, and tools at scale Translate machine learning and deep learning solutions into scalable production implementations Build tools and platforms at scale to improve performance, increase velocity, or optimize workloads Identify significant new roadmap opportunities and influence roadmap prioritization Apply specialized domain knowledge to identify opportunities and influence prioritization of improvements to existing model architectures, methods and approaches Collaborate with cross-functional partners and team to identify opportunities to improve our platform Provide hands-on technical guidance and mentorship for team members Autonomously lead planning and execution for complex problem spaces and major cross-team initiatives Work directly with partner teams and stakeholders to own projects which address related problems, and help set technical direction for projects owned by others Work autonomously, relentlessly prioritize, and collaborate with team members across time zones Advocate for technical quality and engineering best practices What you’ll have 6+ years of hands-on Data Science or ML Engineering experience (4+ if you have a PhD) 4+ years of hands-on experience in one of the following technical domains.
machine learning, recommendation systems, pattern recognition, NLP, artificial intelligence, or a related technical field Proficiency with 1+ programming language(s) (e.
.
Python) Ability to communicate effectively with both technical and non-technical stakeholders We understand that not everyone will match each of the above qualifications.
However, we also realize that everyone has unique experiences that can add value to our company.
Even if you think your background might not perfectly align, we'd love to hear from you! Life at Udemy We aspire to be as vibrant and dynamic as the communities we serve, as inquisitive as those who use our platform, and as revolutionary as the future we strive to open for everyone.
Here are some of the things we love about life at Udemy.
We’re invested in creating an inclusive environment that welcomes a diverse range of backgrounds and experiences.
From creating employee resource groups, ensuring we’re a Fair Pay Workplace, and building a flexible work culture, our belonging, equity, diversity, and inclusion (BEDI) initiatives always put our people first.
We want you to be able to bring your authentic self to work because when we all do, we’re better for it.
Learning is what we do – inside and out.
Our Learning & Development team is second to none, helping ensure your journey is one of continuous progression.
You’ll also have unlimited access to Udemy courses, monthly UDays (meeting-free professional development days), and a generous annual professional development stipend.
Our reason to exist is to revolutionize learning – that calls for taking risks and learning from failures.
Whether it’s our hackathons (a company-wide effort to envision new possibilities for our product) or sharing our prototypes, we see experimentation as a crucial step on the path to success.
We’re committed to creating world-class employee experiences and are proud of the recognition of this by Great Place to Work and Built In Best Places to Work.
Of course, the best thing about being part of Udemy is knowing your work makes a difference for people and organizations around the world.
You’ve got the skills; why not use them to help others develop theirs? At Udemy, we value diversity and inclusion and consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition, or disability.
If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at .
We will consider for employment qualified applicants with arrest and conviction records.
Udemy Mexico Benefits Our benefits are designed to support you and your family with the protection and care you need, ensuring easy access to the right coverage when it matters most.
Here’s a snapshot of the key benefits for full-time Udemates based in Mexico.
Core Benefits.
Medical, Dental, and Vision Coverage.
Includes maternity, private hospital, dental, and vision benefits for employees and eligible dependents.
Life Insurance.
12x monthly base salary, with a Free Cover Limit of MXN 7.
million.
Financial Benefits.
Grocery Vouchers.
Monthly vouchers valued at $ MXN.
Teleworking Allowance.
$800 MXN monthly.
Savings Fund.
Both you and Udemy contribute 13% of your monthly salary, capped to 1.
times the UMA value.
Christmas Bonus.
Equivalent to 30 days of your current salary.
Vacation Bonus.
25% premium on your vacation days.
Time Off Benefits.
Holidays.
Udemy observes 12 public holidays in Mexico.
Annual Leave.
12 days of annual leave per year.
Sick Leave.
10 days of paid sick leave per year.
Family Bonding.
12 weeks of maternity leave or partner leave for bonding after the birth or adoption of a child.
Bereavement Leave.
Up to 20 working days for the loss of a loved one.
Wellbeing Benefits.
Maven (Reproductive Health).
Unlimited virtual appointments and $ lifetime benefit for fertility, adoption, and surrogacy.
Modern Health (Therapy and Coaching).
10 sessions with therapists and 10 sessions with coaches per year.
Origin (Financial Planning).
Free access to Certified Financial Planners for you and your spouse.
Workplace Options (EAP).
24/7 support for family, stress, caregiving, financial, and legal issues.
Additional Perks.
Udemy Courses.
Free and unlimited access to Udemy’s Marketplace and Udemy Business.
Home Office Reimbursement.
$500 one-time reimbursement and $35 monthly for work-from-home needs.
At Udemy, we strive to be transparent around compensation.
Actual compensation for this role is based on several factors, including but not limited to job-related skills, qualifications, experience, and specific work location due to differences in the cost of labor.
In addition to a base salary, this role is also eligible for benefits and equity.
Hiring Compensation Range $ MXN
Detalles de la oferta
- Udemy
- En todo México
- Sin especificar - Sin especificar
- Sin especificar
- 21/11/2024
- 19/02/2025
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