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For Companies At a Glance
- Tasks: Lead a team to develop cutting-edge ML solutions and drive innovative projects.
- Company: Join Amazon India, a leader in tech innovation and machine learning.
- Benefits: Enjoy a diverse workplace, career growth opportunities, and inclusive culture.
- Why this job: Tackle unique challenges daily while making a real impact in the tech world.
- Qualifications: 3+ years in ML management; expertise in ML, NLP, and analytics required.
- Other info: Amazon values diversity and offers support for applicants with disabilities.
The predicted salary is between 43200 - 72000 £ per year.
The Amazon India ML team is developing state-of-the-art, large-scale Machine Learning methods and applications involving terabytes of data. The group focuses on Deep Learning problems in:
- Sponsored Products: the group will be responsible for growing Ads business through semantic matching of customer query to products, automated bidding for sellers, and matching Ads to customer videos on MiniTV.
- Personalisation: the group will be developing state-of-the-art ML models for targeting and automating marketing campaigns to customers with the goal of growing the category business in India.
Key Job Responsibilities
You will be responsible for building a team of scientists who are experienced in taking an idea to reality – from prototype to a customer-facing product, their career development, as well as the road map definition and prioritization for the organization. You will be expected to be heavily entrepreneurial in style and experienced to develop a business plan as well as dive deep into the scientific and technical details of the technology your team is building. This team also publishes our research in the best venues internationally.
As part of this team, you will take on challenging, novel problems every day and collaborate with cross-functional teams. You\’ll need to be comfortable with a degree of ambiguity that’s higher than most projects and love the idea of solving problems that have never been solved before. You will provide ML thought leadership to technical and business leaders and have a demonstrated ability to think strategically about business, product, and technical challenges.
BASIC QUALIFICATIONS
- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval, and Analytics
PREFERRED QUALIFICATIONS
- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems, especially involving deep learning, machine learning, and computer vision, that have been successfully delivered to customers
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit this link for more information.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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Applied Science Manager employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Science Manager
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and deep learning, especially in areas like NLP and information retrieval. This knowledge will not only help you understand the technical requirements of the role but also demonstrate your passion for the field during discussions.
✨Tip Number 2
Network with professionals in the machine learning community, particularly those who have experience in building teams or products. Engaging in conversations with them can provide insights into the challenges they faced and how they overcame them, which could be valuable in your interviews.
✨Tip Number 3
Prepare to discuss your leadership style and experiences in managing teams. Think about specific examples where you successfully guided a project from concept to delivery, as this aligns closely with the responsibilities of the Applied Science Manager role.
✨Tip Number 4
Showcase your entrepreneurial mindset by thinking of innovative solutions to common problems in machine learning applications. Be ready to share your ideas on how to approach ambiguity and tackle novel challenges, as this is a key aspect of the job.
We think you need these skills to ace Applied Science Manager
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications required for the Applied Science Manager position. Familiarise yourself with Amazon's focus on machine learning, deep learning, and the specific projects mentioned in the job description.
Tailor Your CV: Craft your CV to highlight relevant experience in machine learning, team management, and any successful projects you've led. Use specific examples that demonstrate your ability to take ideas from prototype to customer-facing products.
Write a Compelling Cover Letter: In your cover letter, express your passion for machine learning and your entrepreneurial spirit. Discuss how your background aligns with Amazon's goals and how you can contribute to their innovative projects.
Showcase Leadership Skills: Emphasise your experience in building and leading teams. Provide examples of how you've developed team members and defined roadmaps for projects, as this is a key aspect of the role.
How to prepare for a job interview at Amazon
✨Showcase Your Leadership Skills
As an Applied Science Manager, you'll be expected to build and lead a team. Be prepared to discuss your previous management experiences, how you've developed talent, and your approach to fostering a collaborative environment.
✨Demonstrate Technical Expertise
Make sure you can talk in-depth about machine learning, deep learning, and NLP. Be ready to explain complex concepts in a way that shows your understanding and ability to apply them in real-world scenarios.
✨Prepare for Problem-Solving Questions
Expect to face challenging, novel problems during the interview. Practice articulating your thought process when tackling ambiguous situations and how you would approach solving unique problems in ML.
✨Align with Business Goals
Understand how machine learning can drive business outcomes. Be ready to discuss how you've previously aligned technical projects with business objectives and how you plan to do so in this role.
