Staff Software Engineer, Machine Learning

Attentive
US
Hybrid

Who this role is best for

Aimed at senior machine learning engineers who have led cross-functional projects and built scalable ML systems in a fast-paced startup environment.

Best fit for

  • Senior engineers with 6+ years of experience building and maintaining large-scale ML systems.
    — “You have worked professionally building systems for 6+ years
  • Technical leaders who advocate for long-term system improvements beyond immediate tasks.
    — “You are constantly improving the quality of the project you are working on
  • Collaborators comfortable working with cross-functional teams on data-driven products.
    — “working with cross-functional teams

Things to consider

  • The role expects high ownership and proactive system quality measures.
    — “You will operate with a high degree of ownership
  • The salary range is explicitly tied to role, level, and location.
    — “Our salary ranges are determined by role, level and location

How to stand out

  • Highlight specific instances where you scaled ML systems in production.
    — “build scalable systems and data-driven products
  • Demonstrate experience with the listed tools like TensorFlow and PyTorch.
    — “Experience with TensorFlow/Pytorch, xgboost, pandas, matplotlib, SQL, Spark or similar tools
  • Showcase leadership in cross-functional ML projects.
    — “You have led cross-functional machine learning projects across teams
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Senior

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • build production-grade ml systems
  • drive real-time personalization
  • maintain high quality standards
  • lead cross-functional ml projects
Typical background
6+ years experience in ml and data analysistrack record of building scalable systems

Skills & requirements

Required

Machine-learningTensorFlowPyTorchPandasMatplotlibSQLSparkPythonScalable-systemsData-driven-productsCross-functional-teams

Preferred

KubernetesAWSIstioDatadogTerraformCloudflareHelmJavaSpring-bootDynamodbKinesisAirflowPostgreSQLPlanetscaleRedisReactTypeScript

Stack & domain

TensorFlowPyTorchXgboostPandasMatplotlibSQLSparkPythonMachine LearningData AnalysisScalable SystemsData-driven ProductsCross-functional TeamsKubernetesAWSIstioDatadogTerraformCloudflareHelmJavaSpring BootDynamodbKinesisAirflowPostgreSQLPlanetscaleRedisReactTypeScriptCollaborationTechnical LeadershipCommunicationQualityTesting TechniquesProactive StepsLong-term AdvocacyHigh ImpactFast-pacedLate-stage StartupAi MarketingPersonalizationSmsRcsEmailPush NotificationsReal-time Behavioral InsightsCustomer RelationshipsBrandsPeopleConnectAi-powered Personalization EngineProduction-grade Ml SystemsPersonalized ExperiencesHigh-impact Environment

About the role

Original posting from Attentive via Greenhouse

Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.

 

Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.

 

With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups, Forbes’ Cloud 100 (five years running!), Inc.’s Best Workplaces, and the Human Rights Campaign Foundation's Corporate Equality Index!About the Role

Our Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. As a Senior Machine Learning Engineer, you will play a critical role in building, scaling, and operating production-grade ML systems that drive real-time personalization across the Attentive platform.

You will operate with a high degree of ownership, partner closely with Product and Engineering, and help raise the technical bar across our ML systems in a fast-paced, high-impact environment.

What You’ll Accomplish

You have a proven track record of building systems that maintain a high bar of quality

You deeply loathe regressions and take proactive steps to protect against them through a variety of testing techniques

You are a collaborator, technical leader, and a great communicator

You are constantly improving the quality of the project you are working on, both via direct contributions as well as long-term advocacy for larger-scale changes

You are enthusiastic about the high impact, fast-paced work environment of an late-stage startup

10+ years experience is ideal

Your Expertise

You have worked professionally building systems for 6+ years with experience on a single system long enough to see the consequences of your decisions

Experience with TensorFlow/Pytorch, xgboost, pandas, matplotlib, SQL, Spark or similar tools

You have proficiency or experience with Python

You have extensive experience using machine learning and data analysis, or similar, to build scalable systems and data-driven products, working with cross-functional teams

You have a proven track record of building scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation from modern research

You have led cross-functional machine learning projects across teams

What We Use

Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS

Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm

Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS

Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright

Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

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 $320,000 - $360,000 annually + equity + benefits

Our salary ranges are determined by role, level and location

#LI-EF1

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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. 

Source: Attentive careers (Greenhouse)

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