The Senior Software Engineer will develop and optimize the Machine Learning platform, enhancing ML lifecycle tools and supporting high-performance ML practices.
Attentive® is the AI-powered mobile marketing platform transforming the way brands personalize consumer engagement. Attentive enables marketers to craft tailored journeys for every subscriber, driving higher recurring revenue and maximizing campaign performance. Activating real-time data from multiple channels and advanced AI, the platform personalizes content, tone, and timing to deliver 1:1 messages that truly resonate.
With a top-rated customer success team recognized on G2, Attentive partners with marketers to provide strategic guidance and optimize SMS and email campaigns. Trusted by leading global brands like Neiman Marcus, Samsung, Wayfair, and Dyson, Attentive ensures enterprise-grade compliance and deliverability, supporting trillions of interactions across more than 70 industries. To learn more or request a demo, visit www.attentive.com or follow us on LinkedIn, X (formerly Twitter), or Instagram.
Attentive’s growth has been recognized by Deloitte’s Fast 500, Linkedin’s Top Startups and Forbes Cloud 100 all thanks to the hard work from our global employees!
About the Role
We’re looking for a self-motivated, highly driven Senior Software Engineer to join our Machine Learning Platform (MLOps) team. As a team, we enable Attentive’s Machine Learning (ML) practice to directly impact Attentive’s AI product suite through the tools to train, inference, and deploy ML models with higher velocity and performance, while maintaining reliability. We build and maintain a foundational ML platform spanning the full ML lifecycle for consumption by ML engineers and data scientists. This is an exciting opportunity to join a rapidly growing ML Platform team at the ground floor with the ability to drive and influence the architectural roadmap enabling the entire ML organization at Attentive. This team and role is responsible for building and operating the ML data, tooling, serving, and inference layers of the ML platform. We are excited to bring on more engineers to continue expanding this stack.
What You'll Accomplish
- Expand, mature, and optimize our ML platform built around cutting edge tooling like Ray, MLFlow, Metaflow, Argo, and Spark to support traditional, deep learning, and reinforcement learning ML models
- Build and mature capabilities to support CPU / GPU clusters, model performance monitoring, drift detection, automated roll-outs, and improved developer experience
- Build, operate, and maintain a low-latency, high volume ML serving layer covering both online and batch inference use cases
- Orchestrate Kubernetes and ML training / inference infrastructure exposed as an ML platform
- Expose and manage environments, interfaces, and workflows to enable ML engineers to develop, build, and test ML models and services
Your Expertise
- You have been working in the areas of ML Platform / MLOps for 5+ years, and have an understanding of gold standard practices and best in class tooling for ML
- You have owned and built core components of an ML Platform using tools such as Spark, Ray, MLFlow, Kubeflow, or Metaflow
- Python is your coding language of choice, and you’ve worked with Python as both a batch analysis tool and online service framework
- Your passion is exposing platform capabilities through interfaces that enable high performance ML practices, rather than designing ML experiments (this team does not directly develop ML models)
- You understand the key differences between online and offline ML inference and can voice the critical elements to be successful with each to meet business needs
- You understand the importance of CI/CD in building high-performing teams and have worked with tools like Jenkins, CircleCI, Argo Workflows, and ArgoCD
Sample Projects
- Design and implement an online inference pipeline with champion/challenger shadow model testing
- Scale real-time feature streaming use cases to handle low-latency, high-volume RL use cases
- Build a universal data access layer (DAL) and serving interface to expose predictions to different parts of Attentive’s products
- Mature platform interfaces toward full self-service for stakeholders
- Improve existing build and release pipelines for better reliability and Python package management
You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.
For US based applicants:
- The US base salary range for this full-time position is $170,000 - $230,000 annually + equity + benefits
- Our salary ranges are determined by role, level and location
#LI-MDK1
Attentive Company Values
Default to Action - Move swiftly and with purpose
Be One Unstoppable Team - Rally as each other’s champions
Champion the Customer - Our success is defined by our customers' success
Act Like an Owner - Take responsibility for Attentive’s success
Learn more about AWAKE, Attentive’s collective of employee resource groups.
If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience.
At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.
Top Skills
Argo
Argo Workflows
Argocd
CircleCI
Datadog
Jenkins
Kubernetes
Metaflow
Mlflow
Nagios
New Relic
Ray
Sensu
Spark
Splunk
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