VP of Engineering
Company: Deloitte
Location: Washington
Posted on: June 25, 2022
Job Description:
VP of Engineering
Deloitte Digital's Experience Management team combines software and
services to help clients improve their data management and
decisioning, delivering high value intelligence in real-time to
every marketing and advertising channel.
We're looking for a thought-leader and expert like you to fuel our
continuing innovation and help us scale our team of data engineers
and data scientists. This is a high-profile role in a well-funded
team.
Work you'll do
As VP of Engineering - ML/AI & Analytic Automation you will have
full purview over the development and deployment of software and
assets which bring transformational ML/AI capabilities to large
clients. You will combine leading open source tooling and
techniques with a suite of customer experience libraries and
solutions which intelligently automate the management of
cross-channel communications for large clients. We have a great
team of machine learning experts, data scientists, infrastructure
engineers and technical writers, all of whom are committed to
delivering first class software for downstream clients. Our
existing stack makes heavy use of the Python machine learning
ecosystem, and assembles systems to deliver massive decisioning
throughput, with tight latency constraints. Our solutions may be
used to service specific enterprise client marketing and
advertising performance needs, but are designed to support major
ML/AI transformations that service large numbers of professional
data engineers and data scientists in large enterprises. If you
have deep experience in designing, implementing, automating and
deploying machine learning pipelines and workflows in the
marketing, customer experience or advertising spaces, we want to
hear from you!
Your responsibilities will include:
- Work directly with the CTO and peer VPs to drive the technical
vision throughout the engineering team
- Lead a team of 15-20 talented engineers and data scientists
with deep domain knowledge
- Evangelize high quality technology and software development
processes within the firm, working closely with other teams
delivering modern software assets
- Develop enterprise grade machine learning automation
capabilities that hugely reduce cost-per-output-decision, moving
expensive human-driven decisions to lower cost and more performant
machine-driven ones
- Advise on functional requirements for the deployment of
productized technology on client engagements
- Work closely with our product team to guide the vision and
roadmap of the decisioning offering
- Represent the ML/AI and Analytic Automation capabilities and
technologies to others in the broader team and across the firm
- Integrate with surrounding technology components and
services
- Coach senior and junior team members, advocating and advising
them on their career growth
Successful skillsets for this role are:
- Deep expertise in data science and modern software development,
as well as with running engineering teams of this size
- Eagerness to work with other talented teams building other
components of a broader end-to-end capability that converts
ingested data into improved monetary outcomes for clients.
- Strong commitment to the tenets of high-quality software
development
- Care and concern for the well-being of team members who will
look to you for guidance
Our Team
You'll join an existing team of passionate, talented hybrid ML
engineers and R&D data scientists and who collaborate to
design, build and maintain cutting-edge machine learning solutions
that provide our clients with real-time customer intelligence that
controls interactions with consumers. If you're intellectually
curious, hardworking and solution-oriented, you'll fit right into
our fast-paced, collaborative environment.
Qualifications
10+ years of experience architecting and overseeing the development
of significant analytic automation products:
- Deep knowledge in the machine learning lifecycle, and in ways
to facilitate collaboration and productivity in each of its phases.
Exposure to a number of data scientists and expertise in finding
solutions to workflow problems.
- An ability to apply multiple management strategies
- Knowledge of common machine learning frameworks and libraries
and in ways to productionalize their inputs and outputs.
- Comfort with various machine learning techniques and their
practical implementation, from predictions of single dependent
variables, to meta-tagging automation, NLP/NLG, and online methods
such as reinforcement learning
- Experience with one or more common workflow / pipelining
frameworks (Kubeflow, MLFlow, Argo or equivalents)
- Strong knowledge of the Python ecosystem, the Jupyter ecosystem
(Lab, Notebook, Binder) and their libraries, norms and tooling
- Exposure to AutoML tooling (H2O, DataRobot or equivalents)
- 5+ years of experience with large consumer data sets used in
performance marketing
- 5+ years of experience delivering software to large
enterprises
- 5+ years of experience overseeing distributed, high throughput
and low latency architectures
- 3+ years of experience architecting software on top of major
container technology (Kubernetes, docker, or similar).
- Proven ability to communicate both verbally and in writing
within a high performance, collaborative environment.
- A history of good collaboration with DevOps and Project
Managers on meeting project goals.
- Proven track record working with products from major cloud
providers (AWS, GCP, Azure, etc.)
- Bachelor's Degree required: degree in computer science, data
science, engineering, math or similar/related field preferred
- Limited immigration sponsorship may be available
- Ability to travel up to 50%, on average, based on the work you
do and the clients and industries/sectors you serve
Keywords: Deloitte, Washington DC , VP of Engineering, Executive , Washington, DC
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