Design, develop and document cutting-edge ML solutions, using existing and emerging technology platforms
Architect extensible technical architectures to deliver the latest in machine learning, AI, and other emerging technology solutions
Provide technical vision, technical solutions and directions to build modern Machine Learning Platforms, Tooling and Services for ML/AI at Scale.
Contribute to building a platform to streamline all phases of data-centric innovation, including data organization, data access, data exploration, data science prototyping, productionization, testing, and ongoing monitoring of machine learning pipelines
Evangelize and drive adoption of the ML platform, and strive for operational excellence
Oversee the day-to-day operation of the platform, ensuring high availability, scalability and performance and a data-driven approach to continuous measurement and optimization
Integration
Defines architecture blueprints for end-to-end systems to including integration of applications, systems, platforms and technical infrastructure
Design infrastructure, tools, utilities, and automated workflows
Operate as a trusted advisor for the Machine Learning space, helping to shape use cases and implementation in an integrated manner
Support the productionization and deployment of data science models and pipelines
Optimization
Define standards and create reference implementations pattern for machine learning / AI solution and Azure PaaS
Responsible for successful analysis, high-level design and delivery of cloud projects
Partner with data scientists and machine learning engineers to review and co-optimize technical designs
Optimize machine learning and relevant data processing code for scale and robustness
Cost Management
Facilitate in determining architecture goals, cost estimating solutions and reviewing existing cloud deployments for potential improvements to design, availability, recoverability and cost optimization
Engage in a highly collaborative team environment where your expertise is required to suggest best options to lay foundations for cloud data architecture, scaling, and data development opportunities, cost savings, and vulnerabilities
Partner with business stakeholders, management, and technology teams to identify needs and guide the delivery of cost-effective, high-performance technology capabilities leveraging enterprise information architecture principles and core data assets
Qualifications:
Knowledge of Azure relevant certifications such as Azure Solutions Architect, Azure AI Engineer
Deep knowledge in the Machine Learning and data space including designing, building, optimizing and scaling data-intensive ML solutions using distributed computing
Ability to see and implement patterns that enable solution simplification
Ability to influence through persuasion
Experience:
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or other Engineering fields or equivalent experience
5+ years of experience in an architecture or engineering role focusing on machine learning models and deploying them into production at scale
Experience with next generation architectural concepts, including Integrations, advanced analytics, cloud analytics, big data, artificial intelligence, and/or machine learning
Expertise in Python and SQL, with working experience in Apache Spark, Hadoop, Databricks, Snowflake, or other big data systems
Experience working with DevOps on prem or in cloud environments, including but not limited to Deep understanding of compute, storage, networking, Docker/Containers, Kubernetes, cloud APIs and IaaS
Experience with orchestration frameworks
Experience with natural language processing or deep learning frameworks such as Tensorflow, Pytorch, or HuggingFace, etc
Strong analytical and problem-solving skills
Self-motivated individual that thrives in a dynamic environment