Wavicle Data Solutions is hiring a
Lead ML/AI Engineer

Summary

Join Wavicle Data Solutions, LLC as a Lead ML/AI Engineer in Oak Brook, IL and lead data strategy and ML/AI strategy projects, develop AI models, create data systems, plan automated solutions, oversee AI infrastructure development, research and integrate machine learning infrastructure, collaborate with teams to create viable solutions using ML and AI models.

Requirements

• Bachelor’s Degree in Computer Science, Computer Engineering, Information Systems, or a related field
• 48+ months of related experience
• Data, Analytics & AI certifications in Azure, AWS, GCP or SnowFlake
• 3+ years of experience in the following: Architectural patterns and anti-patterns of large high-scale consumer applications; Developing data and analytics solutions; Developing and deploying machine learning systems into a production environment; Azure Technologies such as Azure Functions, Azure API Management, Azure Even Grid, Azure Service Bus, and AWS Services; Professional engineering in a platform team
• 4+ years of experience in the following: Professional consulting in IT Programming and application development

Responsibilities

• Provide a platform for Data Scientist to access data and processes to allow them to fine tune the models
• Build a system that can provide capabilities for Data Scientists to be contributors
• Leverage cloud compute to build solutions
• Understand Data science/ML/AI needs and translate them into workable solutions
• Mentor and guide other ML engineers, scientists, and senior leaders. Be a continuous learner and invest in the learning and development of ML engineers
• Lead data strategy and ML/AI strategy projects
• Develop AI models that align with business goals and support improvements in efficiency and performance for activities in sales, marketing, and business information processes
• Create data systems for departments or teams to integrate into organizational processes, including data ingestion and transformation infrastructure
• Plan and develop automated solutions for organizational and technical operations
• Oversee the development of AI infrastructure for use in consumer systems and products
• Research and integrate machine and deep learning infrastructure to create security applications that protect sensitive data
• Collaborate with data scientists, software developers and machine learning engineers to create viable solutions using ML and AI models
• Lead advanced analytics capabilities for the competency of client
• Help in writing SOWs, proposals and working with Sales initiatives
• Interface closely with product management, engineering, DevOps, labeling, and sales teams to build roadmap in supporting the long-term vision of the team
• Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
• Work with large scale computing frameworks, data analysis systems and modeling environments
• Apply deep learning technologies to give computers the capability to visualize, learn and respond to complex situations
• Design and implement key components of the Machine Learning Platform infrastructure and establish processes and standard methodologies
• Work multi-functionally with data scientists, data engineers, and IT teams to design, develop, deploy, and integrate high-performance, production-grade machine learning solutions and data intensive workflows
• Partner with data scientists and data engineers to create and refine features from underlying data and build reproducible feature pipelines to train models and serve features in production
• Partner with data platform and operations teams to solve complex data ingestion, pipeline, and governance problems for machine learning solutions
• Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads
• Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers

Benefits

Telecommuting is permitted. Ability to work 40 hours/week