coverPhoto
SupportLogic5.0
Engineering: Machine Learning Engineer
Santa Clara, CA
Apply Now
Rating Highlights
Compensation & Benefits: 5.0
Culture & Values: 5.0
Career Opportunities: 5.0
Work/Life Balance: 5.0
Job & Company Insights
Job Type: Full-time
Job Function: machine learning engineer
Industry: Information Technology
Size: 1 to 50 Employees
Job

Engineering: Machine Learning Engineer

We are seeking a Machine Learning Engineer interested in working with data scientists and software engineers to ensure ML models are deployed into production efficiently, effectively, and with high confidence in customer-facing predictions.


About SupportLogic

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures). Privileged to have customers who are big fans of our product and proud of our 100% renewal rate with existing customers. We are a distributed team spread across the United States as well as internationally.

SupportLogic is building a new category of software that leverages natural language processing (NLP) and machine learning (ML) to empower businesses to improve their customer relationships, products, and operations. SupportLogic provides an abstraction layer for conventional ticketing systems (Systems of Record) such as SalesForce Service Cloud, Zendesk, JIRA, Dynamics and continuously analyzes the content of the ticketing system to provide intelligent recommendations and actionable insights in real-time.

About the Data Science Team

The mission of the SupportLogic Data Science team is to create cutting-edge machine learning (ML) models that can extract new signals from unstructured data and make insightful, actionable predictions for our customers.

We are responsible for:

  • Advancing the frontier of ML performance and Intellectual Property (IP) in order to maximize the value of SupportLogic to our customers
  • Working with the Data Platform group to ensure ML models have a smooth path to production
  • Working with the product design and UI teams to maximize the value of our predictions for our end users and customers

We are seeking a Machine Learning Engineer interested in working with data scientists and software engineers to ensure ML models are deployed into production efficiently, effectively, and with high confidence in customer-facing predictions.

You will be working in a fast-moving and growing company; applicants should be self-starting and comfortable learning and using new technologies, systems, and processes.

About the Machine Learning Engineer Role

Responsibilities:

  • Deploy, monitor, and manage Machine Learning models
  • Work with data scientists to provide high-quality ML model features efficiently in order to accelerate their research
  • Work with data scientists to ensure ML model features are transferable to production environments, accelerating the path to production for new models
  • Identify and rectify inefficiencies in data scientist workflows in order to accelerate model iteration and improvement
  • Design and implement APIs or other means of gathering feedback to enable automated model iteration
  • Harden and improve research-grade code into production-grade code before model deployment
  • Design and implement APIs or other interfaces for model input/output in production
  • Design and build test harnesses for ML models and/or APIs to ensure high-quality results before deploying new models to production
  • Recommend ways to improve data reliability and quality and implement them if possible

Required skills and competencies:

  • Located in the United States (due to customer data access requirements)
  • 4+ years of professional software development experience
  • 2+ years of experience as a full-time data scientist, data engineer, or machine learning engineer
  • B.S., degree in Computer Science, Mathematics, or similar quantitative field of study
  • Fluency in Python, and experience with common data science libraries, such as Pandas, numpy, and scikit-learn
  • Experience working with machine learning models in a production and/or customer-facing environment
  • Experience building APIs in Python, especially Flask and/or FastAPI
  • Experience with docker in a professional environment
  • Experience working on or with cloud platforms (AWS, GCP, Azure)
  • Experience with SQL databases and SQL queries
  • Self-starting, with the interest and passion to contribute in a fast-paced startup environment

Nice-to-have skills and competencies:

  • M.S., in Computer Science, Mathematics, or similar quantitative field of study
  • Prior startup experience
  • Experience monitoring and measuring performance of machine learning models in a production environment
Show more
Get alerts to jobs like this, to your inbox.

Suggested Searches