Outreach

Outreach

Outreach offers an AI-powered revenue workflow platform designed to enhance the productivity of sales, marketing, RevOps, and go-to-market teams by automating processes that help in efficiently managing accounts, forecasting, and closing deals.

Internet Software & Services
1K-5K
Founded 2014
$489M raised

Description

  • Design, implement, and improve machine learning systems and models for production use.
  • Contribute to ML applications end-to-end from research and prototyping through production deployment.
  • Reconstruct customer engagement workflows from data and develop metrics to measure their success and efficiency.
  • Build tools and services that support optimization of engagement workflows and product features.
  • Collaborate with product managers, designers, customers, data scientists, ML engineers, and application engineers to define product vision and strategy.
  • Build and maintain microservices and infrastructure for deploying and running ML models in production.
  • Develop and deploy GenAI-based applications and integrate generative components where appropriate.
  • Work with distributed data processing frameworks and ML lifecycle tools to scale analytics and models (e.g., Spark, Databricks, MLflow).
  • Rapidly prototype, experiment, and iterate on solutions and provide hands-on technical leadership to deliver customer-facing features.

Requirements

  • 7–10 years of industry or equivalent experience in machine learning, data science, or a related field.
  • Degree in Computer Science, Data Science, or a related field.
  • Strong programming skills in at least one object-oriented language (Java, Scala, C++, Python, Golang).
  • Substantial experience building and managing infrastructure for deploying and running ML models in production.
  • Experience developing and deploying GenAI-based applications; experience with LangChain or LangGraph is a plus.
  • Experience building microservices; Golang experience is a plus.
  • Experience with distributed data processing frameworks such as Spark; familiarity with Spark MLlib, AWS, Databricks, and MLflow is a plus.
  • Solid knowledge of statistics and machine learning with practical experience applying them to real-world problems.
  • Ability to work collaboratively with cross-functional teams and communicate product vision and strategy.
  • Hands-on, able to quickly learn new tools and languages, and comfortable experimenting to deliver solutions.

Interested in this position?

Apply directly on the company website

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