Deloitte VP of Engineering in San Jose, California
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
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.
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
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.