Deloitte AI/ML Ops - Manager in St. Louis, Missouri
Are you an experienced, passionate pioneer in technology - a solutions builder, a roll-up-your-sleeves technologist who wants a daily collaborative environment, think-tank feel, and share new ideas with your colleagues - without the extensive demands of travel? If so, consider an opportunity with our US Delivery Center - we are breaking the mold of a typical Delivery Center.
Our US Delivery Centers have been growing since 2014 with significant, continued growth on the horizon. Interested? Read more about our opportunity below.
Work you'll do/Responsibilities
Unify machine learning (ML) systems development and ML systems deployment to standardize and streamline the continuous delivery of high-performing models in production
Use statistical and machine learning techniques to create scalable analytics solutions
Develop end-to-end (Data/Dev/ML) Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably
Facilitated the development of objectives by selecting and employing the appropriate SDLC methodologies, and gathering business requirements relevant to ML
Execute best practices in version control and continuous integration/continuous delivery
Operationalize and monitor ML models using high end tools and technologies
Assist in the development and execution of an AI/data governance framework, with a focus on ensuring that AI technologies are well researched and developed
Help administer and work within an AI code of ethics to tackle issues such as privacy, discrimination, data ethics, and promote responsible innovation
Prototype and demonstrate solutions for clients in customer environments
Explain model behavior/results to both technical and non-technical audiences
Collaborate with data scientists, data engineers and other key stakeholders in a fast-paced cross-functional and diverse environment
Stay current on new products and relevant industry trends in the field of ML
Analytics & Cognitive
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The Analytics & Cognitive team leverages the power of data, analytics, robotics, science, and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
Analytics & Cognitive will work with our clients to:
Implement large-scale data ecosystems including data management, governance, and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms.
Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions.
Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise, and providing As-a-Service offerings for continuous insights and improvements.
Solid understanding of the ML lifecycle and concepts
6+ years of experience with the design and implementation (building, containerizing, and deploying end to end automated data and ML pipelines) of automated cloud solutions
6+ years of experience with TensorFlow, Pytorch, and other deep learning frameworks
6+ years of experience with version control tools such as Git
Extensive experience working in an Agile development environment
Fluency in Python, R, and other common ML languages
Fluency in both structured and unstructured data (SQL, NOSQL)
Production experience with Apache Spark
6+ years of hands-on experience with web APIs, CI/CD for ML, and serverless deployment
Familiarity with Linux OS and Windows servers
Knowledge of Docker, Jenkins, Kubernetes, and other DevOps tools
Outstanding analytical and problem-solving skills
Minimum 1 years of relevant experience delivering AI/ML projects
Bachelor's degree or equivalent experience
Certification from any of the three major cloud platforms (AWS / Azure / GCP) in Cloud Architecture / Engineering / DevOps / ML.
Familiarity with Kubeflow or MLflow
Experience with machine learning pipelines (Azure ML)
Familiarity with the latest Natural Language Processing or Computer Vision related algorithms
Must live a commutable distance to one of the following cities: Atlanta, GA; Austin, TX; Boston, MA; Charlotte, NC; Chicago, IL; Cincinnati, OH; Cleveland, OH; Dallas, TX; Detroit, MI; Gilbert, AZ; Houston, TX; Indianapolis, IN; Kansas City, MO; Lake Mary, FL; Los Angeles, CA; Mechanicsburg, PA; Miami, FL; McLean, VA; Minneapolis, MN; Nashville, TN; Orange County, CA; Philadelphia, PA; Phoenix, AZ; Pittsburgh, PA; Rosslyn, VA; Sacramento, CA; St. Louis, MO; San Diego, CA; Seattle, WA; Tallahassee, FL; Tampa, FL; or be willing to relocate to one of the following USDC locations: Gilbert, AZ; Lake Mary, FL; Mechanicsburg, PA.
Ability to travel up to 15% (While 15% of travel is a requirement of the role, due to COVID-19, non-essential travel has been suspended until further notice.)
Limited Sponsorship: Limited immigration sponsorship may be available.
How you'll grow
At Deloitte, our professional development plan focuses on helping people at every level of their career to identify and use their strengths to do their best work every day. From entry-level employees to senior leaders, we believe there's always room to learn. We offer opportunities to help sharpen skills in addition to hands-on experience in the global, fast-changing business world. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career.
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.