Description

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Amazon Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports from a vast catalog. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

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Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. We are building industry-leading Audio, Video and Language technology using GenAI to delight our customers and advance the state-of-the-art in the translation, transcription and generation of multingual cinematic content.
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As part of the AI team in Amazon Prime Video, you will gather requirements from collaborators on research teams in computer vision, audio processing and language modeling and develop scripts and UI tools around creating data pipelines for model training and testing, data/model versioning, dataset curation, data annotations and fix tools, pipelines and QuickSight dashboards as needed. This is critical for our the core technology building. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.
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We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. Your work will impact millions of our customers in the form of products and services that make use of speech and language technology on Prime Video content.

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Key job responsibilities

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a) gathering requirements from scientists
b) extracting data from various in-house and open-source domain
c) developing scripts and UI tools for creating data pipelines for model training and testing, data/model versioning to ensure model reproducibility, train/test dataset curation, data annotations, data cleaning (eliminating ground truth noise or inconsistencies in data)
d) fixing tools, pipelines and QuickSight dashboards as needed
e) creating Sagemaker batch transform scripts
f) automated monitoring of batch transform/aws batch jobs/chaining of dependent jobs
g) making science code deployment ready to hand over to engineering for deployment (creating docker images, setting up of deployment packages etc.)
h) Proficiency using numpy, pandas, kind of libraries, dealing with jsons, csv files, parquet format etc.

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Basic Qualifications

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- Experience in automating, deploying, and supporting infrastructure
- Experience programming with at least one modern language such as Python, Ruby, Golang, Java, C++, C#, Rust
- Experience with Linux/Unix

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Preferred Qualifications

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- Experience with CI/CD pipelines build processes
- Knowledge of and proficiency in the use of Python scripting language
- Knowledge of distributed, multi-tiered systems, algorithms, and relational databases
- Experience building machine learning pipelines, MLOPs, dataset curation is preferred.
- Experience in basic front end technologies for the sake of tooling for annotations/human studies etc.

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