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Machine Learning Engineer



Software Engineering
Posted on Thursday, July 4, 2024

About SupportLogic

SupportLogic SX™ is a platform that elevates customer service experience by leveraging natural language processing (NLP) and machine learning (ML). The platform seamlessly integrates with your existing ticketing system (such as Salesforce Service Cloud, Zendesk, Microsoft Dynamics), reads all the comments in every ticket to extract key signals related to customer sentiment and churn, predicting outcomes and providing proactive recommendations. Customer Support and Success organizations use the platform to stay on top of how their customers feel about them thus improving customer relationships, products and operations.

We are a well-funded startup with investments from top tier investors in Silicon Valley (Sorenson Ventures, Sierra Ventures) and a customer list that is a who’s-who of Enterprise IT companies. We are privileged to have customers who are not only outspoken fans of our product but also prove it by renewing every year.

Note: We support 100% remote work for applicants who reside in the following states: Arizona, California, Colorado, Massachusetts, Minnesota, New Jersey, New York, North Carolina, Pennsylvania, Texas, Washington and West Virginia. Please apply only if you live in one of the listed states.

Overview of role:

The mission of the SupportLogic Machine Learning (ML) team is to create and leverage cutting-edge ML models, especially Large and Small Language Models that can extract new signals from unstructured data and make insightful, actionable predictions for our customers.

We seek a Machine Learning Engineer interested in improving any and all aspects of ML organization efficiency, with the ultimate goal of increasing customer confidence in our ML predictions and our ability to train new ML models or roll out new ML products quickly and efficiently. SupportLogic’s machine learning products are our core value proposition for our customers, so ML efficiency has a direct connection to our value to our customers and as a company.

How your work will support our growth:

  • Ship - Increase velocity of ML model deployment into production through automation of model management, deployment, and rollout processes.
  • Validate - Increase confidence of model rollouts by enriching and automating model validation prior to and immediately after deployment.
  • Measure - Provide insight into accuracy and relevance of ML model predictions in production by measuring and monitoring model input and output data distributions, as well as user engagement/feedback on predictions.
  • Automate - Incorporate user feedback/activity into new ML model training by automation of data collection, model retraining, model measurement, etc., towards a goal of continuous automated model retraining.
  • Build - Provide internal tools or incorporate commercial tools (e.g., ClearML) into data scientist workflows for data analysis, feature generation, model development, etc., to boost ML team productivity.
  • Collaborate - Bridge the gap between ML research and production-grade backend code by working with other engineering teams to integrate new ML models or APIs into production.

About you (don't worry if you don't have this whole list- we expect you to learn with us):

  • A self-starter, with the interest and passion to contribute in a fast-paced startup environment.
  • Comfortable learning and using new technologies, systems, and processes.
  • B.S. degree or equivalent in Computer Science, Mathematics, or similar field of study.
  • 2+ years of professional experience as an MLE, building ML products
  • 1+ years of experience deploying NLP solutions to production environments
  • Strong proficiency in software development and system design
  • Fluent in Python
  • Experienced with common Python data science libraries such as PyTorch, HuggingFace, Pandas, numpy and scikit-learn
  • Experienced with the lifecycle of model training, evaluation and deployment
  • Experienced with using SQL


  • Experience with LLMs in production
  • Experienced building APIs in Python, particularly in FastAPI or Flask.
  • Experienced with using Pytest, Docker, and sqlalchemy
  • Experienced with MLOps platforms such as KubeFlow or MLFlow
  • Experienced with modern data warehouse such as Snowflake, BigQuery or Hive

How we support our employees' growth and well-being:

  • Outstanding healthcare (medical, dental, and vision) covered at 100% for employee+ family
  • 401K
  • Equity (stock options)
  • Unlimited PTO where you're encouraged to take to recharge
  • Remote 1st, collaborative, and transparent culture

The salary range for this role is $120,000- $170,000 annually.

Our commitment to diversity and inclusion is deep and core to the company we're building. Our users are diverse, and we believe that our company needs to reflect the diversity of our users in order to build the best possible product. Discrimination of any type will not be tolerated at SupportLogic, and we pride ourselves in making sure that all employees feel heard, supported, and challenged. To that end, SupportLogic prohibits discrimination on the basis of race, color, religion, creed, sex, age, marital status, national origin, mental or physical disability, political belief or affiliation, veteran status, sexual orientation, gender identity and expression, genetic information, and any other class of individuals protected from discrimination under state or federal law in any aspect of employment and application for employment.

If you are a California resident, please see our CCPA job applicant notice:

View our CCPA Job Applicant Notice