Software Engineer III - Machine Learning Engineer at Walmart

Posted in Other 10 days ago.

Location: Sunnyvale, California





Job Description:

Position Summary...

What you'll do...

The Cortex team is the core A.I. platform powering the vision of
delivering the world's best intelligent personal assistants to Walmart's
customers, accessible via natural voice commands, text messages, rich UI
interactions, and a mix of all of the above via multi-modal experiences.

We believe /conversations/ are a natural and powerful user interface for
interacting with technology and enable a richer customer experiences --
both online and in-store. We are building and designing the next
generation of Natural Language Understanding (NLU) services that other
teams can easily integrate and leverage, and build rich experiences:
from pure voice and text shopping assistants (Siri, Google Assistant,
[Text to Shop]), to customer care channels, to mobile apps with rich,
intertwined, multi-modal interaction modes ([Me@Walmart]).

Interested in diving in?

We need solid engineers with the talent and expertise required to
design, build, improve and evolve our capabilities in at least some of
the following areas:

- Service oriented architecture in charge of exposing our NLU
capabilities at scale, and enabling increasingly sophisticated model
orchestration.

- Since the service takes in traffic for a large set of Walmart
customers (that is 80% of American households!), you will get to
solve non trivial challenges in terms of service scalability and
availability.

- You will design and build the primitives to efficiently orchestrate
model-serving microservices, taking into account their dependencies,
and improving the /combined/ latency and robustness of such
microservices (e.g. fan out in parallel to N services for a single
request, and reply with whichever gives the fastest answer).

- You will also bake-in functionality which can drive improved machine
learning modeling and experimental design, such as A/B testing.

- Model serving and operations

- There is a constant tension between model improvements (more
computations) and model serving latency. So, we are always in a
quest of crunching more numbers, while preserving our SLAs, and
controlling the operational costs.

- You will guide our efforts to always find the best tradeoffs in
terms of architecture, tooling (Tensorflow serving? / ONNYX? /
Triton?) and infrastructure (CPU? / GPU?, GCP? / Azure?) for model
serving -- based on the latest model developments and product
requirements.

- In particular, you will drive principled and scientific load-testing
efforts, to clearly identify the tradeoffs at hands, and
tune/optimize the model-serving stack.

- Tooling, infrastructure and pipelines for reproducible workflow and
models, enabling rapid innovation across the entire product lifecycle.

- You will author and maintain pipelines that safely build and deploy
models to production via continuous deployment.

- You will achieve scalable and efficient resource management
capabilities (cloud infrastructure).

- You will provide robust and built-in diagnostics for quality control
throughout.

- You will integrate -- or build -- labeling tools which can
seamlessly integrate at the heart of our conversation data store
(GCP, BigQuery) and intertwine multiple labeling sources of various
confidence levels.

Come at the right time, and you will have an enormous opportunity to
make a massive impact on the design, architecture, and implementation of
an innovative, mission critical product, used every day, by people you
know, and which customers love.

As part of the emerging tech group, you will also have the additional
opportunity of building demos, proof of concepts, creating white papers,
writing blogs, etc.

Here are some of our team publications:

- Blog Posts

- "Building a conversational assistant platform for voice-enabled
shopping"

- "Using Context to Improve Intent Classification in Walmart's
Shopping Assistant"

- "Making Walmart's Shopping Assistant Proactive"

- Papers & Talks

- Semantic Representation and Parsing for Voice eCommerce (Paper and
Talk) - Vivek Kaul, Shankara B Subramanya, R2K Workshop at KR 2018

- Knowledge Graphs for AI-Powered Shopping Assistants, GraphConnect
2020, Ghodrat Aalipour, Mohammed Samiul Saeef

- Improving Intent Classification in an E-commerce Voice Assistant by
Using Inter-Utterance Context (Paper + Talk) - Arpit Sharma,
e-Commerce & NLP at ACL 2020

Minimum Qualifications

- Solid data skills, sound computer-science fundamentals, and strong
programming experience.

- Deep hands-on technical expertise in full-stack development.

- Programming experience with at least one modern language with an
efficient runtime, such as Scala, Java, C++, or C#.

- Experience with at least one relational database technology such as
MySQL, PostgreSQL, Oracle, or MS SQL.

- Some level of fluency in Python (lingua-franca of our
data-scientists).

- Understanding of the challenge of distributed data-processing at
scale.

- Deal well with ambiguous/undefined problems; ability to think
abstractly.

- Ability to take a project from scoping requirements through actual
launch.

- A continuous drive to explore, improve, enhance, automate, and
optimize systems and tools.

- Capacity to apply scientific analysis and mathematical modeling
techniques to predict, measure and evaluate the consequences of
designs and the ongoing success of our platform.

- Excellent oral and written communication skills.

- Bachelor's degree or certification in Computer Science, Engineering,
Mathematics, or any other related field.

Preferred Qualifications

- Large scale distributed systems experience, including scalability and
fault tolerance.

- Experience taking a leading role in building complex data-driven
software systems successfully delivered to customers

- Relentless focus on scalability, latency, performance robustness, and
cost trade-offs -- especially those present in highly virtualized,
elastic, cloud-based environments.

- Exposure to cloud infrastructure, such as Open Stack, Azure, GCP, or
AWS as well as infrastructure management tech (Docker, Kubernetes)

- Experience building/operating highly available systems of data
extraction, ingestion, and massively parallel processing for large
data sets. In particular experience in building large scale data
pipelines using big data technologies (e.g. Spark / Kafka / Cassandra
/ Hadoop / Hive / BigQuery / Presto / Airflow).

- Hands-on expertise in many disparate technologies, typically ranging
from front-end user interfaces through to back-end systems and all
points in between.

- Familiarity with Machine Learning concepts & processes

- Masters or PhD in Computer Science, Physics, Engineering, Math, or
equivalent.

#EmergingTechGlobalTech

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Bachelor's degree in Computer Science and 2 years' experience in software engineering or related field OR 4 years' experience in software engineering or related field.

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Masters: Computer Science

Primary Location...
640 W California Avenue, Sunnyvale, CA 94086-4828, United States of America


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