Our client is looking for an exceptional Software Engineer to join our growing team. You will be building automation to enable machine learning engineers to continuously deliver predictive analytics for athlete performance, forecasting, personalization, and inventory optimization. You will work with a team of architects, platform engineers, and machine learning engineers to come up with new and interesting models, test them, and productionalize and scale them in the cloud as APIs, stream processing, or massive batch processing. We are looking for a high energy individual with experience developing cloud native applications, APIs, and data pipelines that values automation, testing, and security. You will orchestrate cloud, containers, big data, parallel processing technologies, advanced analytics, machine learning, and deep learning techniques to quantitatively plan product demand, allocate resources, and target the right customers with the best products. Above all, your work will accelerate our client’s core mission of serving Athletes*.

What you'll do

• Build cloud infrastructure for machine learning following the MLOps model
• Design and implement public and internal APIs
• Design event and streaming based services
• Build Tests and Build Pipeline for automated Deployment
• Establish Monitoring and Alerting for custom infrastructure batch data pipelines for machine learning for massive data sets
• Support investigation of new cloud services, software packages/tools, APIs, container management, and distributed systems, to continuously deliver quality analytics and machine learning at scale.
• Collaborate with a cross functional agile team of software engineers, data engineers, ML experts, and others to build new product features
• Enable rapid iteration and product quality through continuous A/B testing
• Design, implement, and maintain solutions/platforms
• Collaborate with platform engineering and architects to utilize best practices and maintain compliance

Who you are

• Rock solid software engineer with demonstrated experience in enabling MLOps.
• Bachelor's Degree in computer science, software engineering, or related field preferred
• Experience with CI/CD infrastructure using Git, Jenkins, or similar tools
• Experience with Docker, Kubernetes, Mesos, containers, and related tools andsystems
• Experience with AWS components and services, particularly, IAM, ECS/EKS, EMR, S3, and Lambda/Serverless
• Prefers infrastructure as code experience with CloudFormation or Terraform
• Strong Python, shell scripting, and SQL
• You care about agile software processes, data-driven development, reliability, and responsible experimentation
• Experience with Spark, Databricks, Snowflake.
• 7+ years of work experience
• Will be the tech lead & representing Engineering

The target hiring compensation range for this role is $65.99 to $73.33 an hour. Compensation is based on several factors including, but not limited to education, relevant work experience, relevant certifications, and location.

About Aquent Talent:

Aquent Talent connects the best talent in marketing, creative, and design with the world’s biggest brands.

Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. We also offer free online training through Aquent Gymnasium. More information on our awesome benefits! 

Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We’re about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.

Global leader in athletic footwear, apparel, and equipment. Our client focuses on innovation, performance, and marketing, partnering with top athletes and teams. The company emphasizes sustainability and digital advancements to enhance the sports experience.