Deloitte AI Engineer - Experience Management in Austin, Texas
Come join a team of passionate, talented "pure" data scientists and hybrid AI engineers who collaborate to design, build and maintain cutting-edge AI solutions that arm our clients with real-time customer insights delivering tremendous value. If you ' re intellectually curious, hardworking and solution-oriented, you ' ll fit right into our fast-paced, collaborative environment.
Work you ' ll do
As an AI Engineer, you ' ll support the development and deployment of transformational AI capabilities for large clients. You ' ll combine leading open source tooling and techniques with a suite of customer experience libraries and solutions, which automate the management of cross-channel communications with consumers for large clients. We make heavy use of the Python machine learning ecosystem, and build systems to deliver massive decisioning throughput, with tight latency constraints on our real-time systems. If you have deep experience in designing, implementing, automating and deploying machine learning pipelines and workflows, we want to hear from you!
Your responsibilities will include:
Participate in all phases of the model development lifecycle
Solution productionalized machine learning to drastically reduce total cost per decision, moving expensive human-driven decisions to drastically cheaper and more effective machine-driven ones
Help design and implement functional requirements for client engagements
Collaborate with our services data scientists to deploy and use libraries and APIs which make machine learning for customer use cases both easy and powerful, and help brands gain deep understandings of their consumers
Prepare technical documentation
Integrate with surrounding technology components and services
Coach junior team members
Successful skillsets for this role are:
Deep interest in data science and software development
Eager to work with data scientists, fellow engineers and product owners
Experienced with collaborative techniques like pair-programming and white board design sessions
Continuously learning and improving, and constantly exploring new languages, tools, and techniques
Advertising, Marketing & Commerce
Our Advertising, Marketing & Commerce team focuses on delivering marketing and growth objectives aligned with our clients' brand values for measurable business growth. We do this by creating content, communications, and experiences that engage and inspire their customers to act. We implement and operate the technology platforms that enable personalized content, commerce and marketing user-centric experiences. In doing so, we transform our clients' marketing and engagement operations into modern, data-driven, creatively focused organizations. Our team brings deep experience in creative and digital marketing capabilities, many from our Digital Studios.
We serve our clients through the following types of work:
Cross-channel customer engagement strategy, design and development (web, mobile, social, physical)
eCommerce strategy, implementation and operations
Marketing Content and digital asset management solutions
Marketing Technology and Advertising Technology solutions
Marketing analytics implementation and operations
Advertising campaign ideation, development and execution
Acquisition and engagement campaign ideation, development and execution
Agile based, design-thinking, user-centric, empirical projects that accelerate results
3+ years of experience authoring, supporting or providing a data science platform to data scientists:
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.
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, particularly 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)
Experience in deploying and maintaining enterprise-scale machine learning applications in production
2+ years of experience writing well-tested production software
1+ years of experience on distributed, high throughput and low latency architecture.
1+ years of experience building software on top of major container technology (Kubernetes, docker, or similar).
Strong testing mindset with experience writing tests at various levels of granularity
Familiarity with Continuous Integration tools (GitHub actions, Travis-CI, etc.)
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.)
Limited sponsorship may be available.
Experience with large consumer data sets used in performance marketing is a major advantage
Exposure and/or expertise writing and/or running Terraform or other infrastructure-as-code automation
Well-versed in (or contributes to) data-centric open source projects
Experience in performance analysis and optimization of machine learning applications, e.g. in optimizing code written by others
Presence or contributions to projects within the wider open source ecosystem
Proven ability to communicate both verbally and in writing within a high performance, collaborative environment.
Exposure to commonly used relational and non-relational databases
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.