Do you want to own cutting edge technology, solve new problems that didn’t exist before, and have the ability to see the impact of your successes?

Amazon and MX Player recently joined forces to accelerate premium free entertainment for 250 million users in India and 50 million users in aditional 26 countries. With this acquisition, Amazon merged two of India’s most popular free AVOD (or ad-supported video on demand) services – MX Player and Amazon miniTV into one service - Amazon MX Player. We seek engineers who can help us shape and build Amazon MX Player.

Amazon MX Player is Amazon's big bet in terms of shaping the future of the free AVOD landscape. We are looking for senior creative leader, who can help shape our brand and creatives for our new exciting show slate. This is an exciting opportunity for someone who wants to work in a start-up like environment and is passionate about building clutter breaking creatives / marketing campaigns to build viewer interest for our new shows.

You can read about the service here: https://www.aboutamazon.in/news/entertainment/amazon-minitv-mx-player-merger https://economictimes.indiatimes.com/industry/media/entertainment/amazon-merges-minitv-with-mx-player-to-create-a-free-streaming-giant/articleshow/114007982.cms

You'll be part of the team which builds unique video viewing experiences for our customers, and the features you build will have a direct impact on the Amazon MX Player customer experience. We are seeking an engineer who can channel their passion for movies and TV entertainment to work backwards from the customer to help us achieve our vision.

In this role, you will develop new features for Amazon MX Player, working with your engineering team, product managers, and UX designers to build products that delight our customers. You will own customer facing features through the entire life-cycle, from design, implementation, testing, deployment and into production. You will work to optimize applications for performance and reliability.

Key job responsibilities
- Ability to code right solutions starting with broadly defined problems.
- Understand basic Algorithm fundamentals.
- Development of code in object oriented languages and build large scale robust distributed systems
- Eagerness to learn newer framework and ecosystems (eg. Android, IOS, React JS, NodeJs

Candidates for this role must have:
- A solid grounding in Computer Science fundamentals (based on a BS or MS in CS or related field)
- Understanding of the tools of the trade, including an understanding of any of modern programming languages (Java / JavaScript / C/C++).
- Proven educational track record with sound data structure and algorithm knowledge

Key job responsibilities:
- Ability to code right solutions starting with broadly defined problems.
- Understand basic Algorithm fundamentals.
- Development of code in object oriented languages and build large scale robust distributed systems
- Eagerness to learn newer framework and ecosystems (eg. Android, IOS, React JS, NodeJs

Key job responsibilities
A day in the life
You are hands-on with developing apps, submitting and reviewing code to set the coding standards bar for our team. You will design and review architectural and software design documents to raise the engineering bar for the team. You will deep dive and provide technical guidance on specific topics (i.e. video playback, application performance, addressing security risks). You will participate in scrum meetings to unblock the team. You will provide input to our quarterly and yearly planning exercises.

Key job responsibilities
1. Design, develop and maintain large-scale recommendation and search systems using machine learning and information retrieval techniques

2. Lead technical architecture decisions and drive complex initiatives across multiple teams to improve search relevance and recommendation quality

3. Partner with Product and Data Science teams to translate business requirements into technical solutions and measurable outcomes

4. Design and implement A/B testing frameworks to evaluate and improve search and recommendation system performance

5. Optimize system performance, focusing on latency, scalability, and reliability of search and recommendation services

6. Drive data-driven decisions through analytics, monitoring, and experimentation to continuously improve system effectiveness