Sr Data Scientist, Search Science AI&ML

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools, Want to enable adoption of large models across teams within Amazon to solve challenging Deep Learning problems!

Come join us and unleash full capability of large model training!

The M5 team is engaged in a multi-year effort to build semantic representations of Amazon-specific entities such as ASINs, queries, customers, sellers, shopping sessions and vend them to machine learning (ML) systems across Amazon. The representations we build will be multi-entity, multi-modal, multi-lingual, multi-locale, and multi-task (M5), and will utilize all available data for each entity, preferably using their combination. The key advantage that the representations will provide is that they will be label efficient, that is, it will be easy to adapt them to a new task using only a handful of labeled data. Moreover, it will be possible to compress the model generating the representations to a lean and efficient model with a small number of parameters for online deployment with tight latency constraints. Initially, we will focus on a subset of applications from Search, Catalog, and Ads, and eventually expand to all major Amazon services and experiences.

At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.

Amazon Search is looking for a Sr Data Scientist (ML /AI), who will be the Subject Matter Expert (SME) for helping technology customers internal and external to design solutions that leverage our deep learning large scale search services. As part of the team, you will work closely with customers to enable large-scale use cases, design ML pipelines, and drive the adoption of AI/ML platforms. You will interact with other Data Scientist , Applied Science teams and engineers in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage AI/ML for large model development and training. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.

You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building complex machine learning models. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help Amazon customers in their selection process

Key job responsibilities

• Working with customers development and data science teams to deeply understand their business and technical needs. After understanding their needs, you will design solutions that make the best use of AI/ML Services.
• Drive adoption of M5 embedding's/products by integrating to AWS services
• Partner with SA's, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment.
• Thought Leadership – Evangelize AI/ML search services and share best practices through forums such as blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, Amazon Summits, etc.
• Act as a technical liaison between customers and the services teams to provide customer driven product improvement feedback.
• Develop and support an M5 internal community of ML related subject matter experts in the Americas and global customers.

BASIC QUALIFICATIONS

• 5+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
• 4+ years working as a Data Scientist
• 5+ years of experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions
• 2+ years of experience with one or more Deep Learning frameworks such as Apache, PyTourch, TensorFlow
• 5+ years professional experience in software development in languages related to ML like Python or R. Experience working with RESTful API and general service-oriented architectures.
• 3+ years of experience in technical architecture, design, deployment and operations for AI platforms, standards, protocols and devices

PREFERRED QUALIFICATIONS

• Graduate degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.)
• 5+ years of industry experience related to large scel model development
• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relationships
• Consulting experience and track record of helping customers with their AI needs
• Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences ·
• Experience with AWS technologies like SageMaker, Redshift, S3, EC2, Data Pipeline development with AWS services & EMR
• Knowledge of SparkML
• Able to write production level code, which is well-written and explainable
• Experience using ML libraries, such as scikit-learn, caret, mlr, mllib
• Experience working with GPUs to develop models
• Experience handling terabyte size datasets
• Track record of diving into data to discover hidden patterns
• Familiarity with using data visualization tools · Knowledge and experience of writing and tuning SQL
• Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
• Experience giving public presentations