Senior ML Ops Engineer

Description

Sprout Social empowers businesses worldwide to harness the immense power and opportunity of social media in today’s digital-first world. Processing over one billion social messages daily, our platform serves up essential insights and actionable information to over 30,000 brands, informing strategic decisions that drive business growth and innovation, and fostering deeper, authentic connections to their end customers. Our full suite of social media management solutions includes comprehensive publishing and engagement functionality, customer care solutions, influencer marketing, connected workflows, and business intelligence. We're actively weaving AI throughout our products to drive our business’s growth trajectory.

What you’ll do

• Build and maintain infrastructure using AWS, Terraform, and Kubernetes to support AI/ML at scale, including Generative AI applications. 
• Manage the end-to-end lifecycle of machine learning models, ensuring observability and tooling support both scale and speed.
• Execute at scale while staying nimble enough to keep up with new capabilities being offered by social network APIs.
• Improve processes and champion ideas that matter while holding the team accountable to high code quality and engineering standards.
• Support our AI/ML Scientists by developing tooling to streamline model development and deployment.
  
  

What you’ll bring

We’re looking for a creative, collaborative, pragmatic, highly motivated, and impact oriented technical leader to join our team in building great software. If you can solve hard problems, deliver quality server-side software, and confidently guide your peers to learn from and teach each other, we’d love to talk with you!

The minimum qualifications for this role include:

• 5+ years of experience developing and supporting AI/ML software in a production environment.
• 5+ years of experience programming in object-oriented languages such as Java, Python, or C++.
• Impact-oriented mindset with an interest in stability at scale and a willingness to engage in feature development.

Preferred qualifications for this role include experience:

• 3+ years of experience developing and supporting scalable, distributed backend services.
• 3+ years of experience building and supporting GPU-heavy services.
• 1+ years of experience with LLMs / Generative AI, including managing their unique costs, constraints, and observability challenges.
• 1+ years of experience with Infrastructure-as-Code (Terraform) and container orchestration (Kubernetes) within AWS environments.
  
  

How you’ll grow

Within 1 month, you’ll plant your roots, including:

• Complete Sprout’s New Hire training program alongside other new Sprout team members.
• Get acclimated to the team's current Mission, Goals, and Objectives along with future product roadmaps.
• Become familiar with the team’s existing deployment patterns and the ML Ops tooling ecosystem.
  
  

Within 3 months, you’ll start hitting your stride by:

• Decomposing work into small, similarly sized units and working with your squad to prioritize quarterly team goals.
• Setting up initial software for model deployment and monitoring of ML models.
  Partnering with the Infrastructure team to deploy an existing ML model in Kubernetes.
  Acting as the domain owner for new projects and writing necessary design documents.
  
  

Within 6 months, you’ll be making a clear impact through:

• Rolling out monitoring and alerting tools to identify problems before they affect users.
• Helping depl