Role will start remotely and transition into onsite once COVID restrictions are uplifted. Candiate should be open for Contract to hire. No sponsorship is available now or in the future.
We are looking for a Machine Learning Solution Architect with experience in defining, building and operating Client workloads.This role is expected to provide thought leadership around architectural best practices by leveraging experience and current industry trends.
In this role, you will continuously sharpen your knowledge around the end-to-end model development lifecycle from data preparation and feature engineering to model deployment and retraining. You will use your expertise to provide recommendations around security, cost, performance, reliability and operational efficiency to accelerate projects.
You will be closely working with leadership teams from the different organization to establish the foundation to create value for diverse business functions such as supply chain, pricing, Industrial IOT & digital factory implementation, digital marketing and sales growth, and will impact business units that span through multiple geographic areas.
Duties and Responsibilities
Understand current state architecture, including pain points.
Create and document future state architectural options to address specific issues or initiatives using Machine Learning.
Innovate and scale architectural best practices around building and operating Client workloads by collaborating with stakeholders across the organization.
Lead the end-to-end model development lifecycle from data preparation and feature engineering to model deployment and retraining.
Provide recommendations around security, cost, performance, reliability and operational efficiency and implement them
Provide thought leadership around the use of industry standard tools and models (including commercially available models and tools) by leveraging experience and current industry trends.
Collaborate with the Enterprise Architect, consulting partners and client IT team as warranted to establish and implement strategic initiatives.
Make recommendations and assess proposals for optimization.
Identify operational issues and recommend and implement strategies to resolve problems.
10+ years of overall experience in Data and Analytics domain in a matrix environment, utilizing various SDLC methodologies
Clear understanding of workflow and pipeline architecture of Client and deep learning workloads
4+ years of experience in Client operations ,MLops and DevOps workflow and tools such as Git, Kubernetes, CloudFormation and others
Working knowledge of databases, data warehouses, data preparation and integration tools, along with big data parallel processing layers such as Apache Spark or Hadoop
knowledge of pure and applied math, Client and DL frameworks, such as Tensorflow, and Client techniques, such as random forest and neural networks, are important.
Working experience with common techniques for analyzing data using advanced analytics tooling (SAS, R, Python, etc.)
Background in Client algorithm development, AI/Client Platforms, Deep Learning, Client Operations in the cloud environment.
Knowledge of relevant languages, tools and frameworks in AWS environment
Ability to collaborate with leaders, users, Data scientist, Data Engineers, vendors, and other IT teams
Ability to work with multiple projects and work streams at one time. Must be able to deliver results based upon project deadlines.
Willing to flex daily work schedule to allow for time-zone differences for global team communications
Strong interpersonal and communication skills