Senior Machine Learning Engineer

TextUs is an award-winning provider of SMS cloud communications with managed CRM and ATS integrations. Instead of waiting days for an email response, our real-time communication combines conversational text messaging, cloud-voice service and personalized automation to help our customers connect with people in real time and build better relationships.

OVERVIEW

The data team at TextUs is helping the business solve challenging problems by discovering actionable insights in the universe of data we have across the company.  We want to leverage state of the art data science tools and techniques to help foster an environment of data-based decision making.  This work has the potential to unlock serious growth opportunities across the business and will be impactful from business operations to product development.  This group is responsible for developing the algorithms, building and optimizing models, and productionizing the necessary data pipelines to power our ML and AI initiatives.  

WHAT YOU'LL DO

• Data Engineering & Pipeline Support:
  • Design and develop data pipelines from a variety of internal and external sources.
  • Build, cleanse, and audit data pipelines to ensure high-quality, reliable outputs.
  • Collaborate with engineers and architects to implement robust data infrastructure.
  • Automate workflows and data processes, integrating third-party data sources and managing foundational schemas.
• Machine Learning & Data Science:
  • Build and deploy machine learning models, developing algorithms that improve over time.
  • Lead all phases of model development: data processing, feature selection, model training, testing, deployment, and monitoring.
  • Use machine learning, NLP, and other technologies to enhance engagement and optimize messaging.
  • Stay up-to-date with AI/ML advancements and share their potential applications with the team.
  • Educate internal and external stakeholders about emerging technologies and promote their practical use.
• Collaboration & Knowledge Sharing:
  • Partner with Product, Engineering, and Business teams to align on product features and integrate ML capabilities.
  • Train team members on using data and machine learning insights.
  • Establish cross-functional processes to incorporate data science into product development.
• Product & Business Insights:
  • Develop user metrics and benchmarks that lead to improved engagement and best practices.
  • Identify key KPIs and design experiments to validate our product developments and business outcomes.
  • Build and maintain analytics dashboards to deliver actionable insights to customers and internal teams.
• Thought Leadership & Innovation:
  • Serve as a thought leader, driving innovation in data-driven capabilities and planning for future advancements.
  • Communicate complex data science concepts in ways that everyone can understand.

WHO YOU ARE

• Experienced Professional:
  • You probably have around 5 years of experience using statistics and machine learning algorithms for several different applications. Or maybe you have a little less practical experience but have other passions and skills that make you the ideal candidate for us to talk to.
  • Proven track record in production environments, including building and improving ML models.
• Technically Proficient:
  • Skilled in programming languages like Python, R, or Scala.
  • Experience fine-tuning Large Language Models (LLMs) for domain-specific applications.
  • Familiar with frameworks like PyTorch or TensorFlow and cloud platforms for hosting models.
• Data Savvy:
  • Proficient with data technologies such as Spark, Presto, Hive, or Hadoop for analyzing large datasets.
  • Solid understanding of data modeling for relational databases, data warehouses, and SQL.
  • Able to translate complex data requirements and facilitate collaboration across teams.
• Excellent Communicator:
  • You excel at distilling complex data analytics and machine learning insights for both technical and non-technical stakeholders.
  • Skilled at presenting data, creating visualizations, and communicating insights to drive informed decision-making.
• Agile Mindset:
  • Experience working within Agile or Lean frameworks.
  • Able to incorporate data science into iterative development processes for continuous product improvement.
• Collaborative Team Member: