Machine Learning Engineer (Remote)

Our world relies on AI more and more each day.  But what does it actually mean for AI to be ‘reliable’?  As you consider the question, are you finding that the rabbit hole grows deeper and deeper?  Does it intrigue you as both a necessary and valuable question for people to answer?  If so, we’d love to meet you.

At Datatron, we create technology to help the growing number of companies sprinting towards reliance on machine learning as part of their operations.  Our combination of model ops and governance products ensure machine learning artifacts created by our customers are easy for them to deploy, highly available, and continuously measured for target performance...regardless of how they were developed.  We help them guard against bias and drift, safely manage the release of new versions, and alert them to potential issues as they arise. We take pride in the unique, agnostic platform we provide and believe we are contributing to the cause of ethical AI; after all, can it fundamentally be ethical if you cannot rely on it?

As a Machine Learning Engineer on our team, you will be developing services which create an integration layer between our platform and our customer’s unique machine learning artifacts.  Quickly you will assess and recommend the right ways to measure effectiveness and detect anomalies, helping to develop configurable governance analytics for models which are necessary to monitor reliability of performance.  You will find means to integrate and interact with different providers of data science tools and ML solutions to extend the options available to customer data scientists, as they enter testing and deployment phases, so that tasks which currently take them weeks and months of effort for each model take hours or days instead, all thanks to you.


We’re looking for people who have:

  • At least 3 to 5 years of full-time coding, preferably with high proficiency in Python
  • Insight into how the operational realities of data science can be better managed and accelerated
  • Significant focus in the past on MLOps, building data pipelines, and evaluating libraries
  • Previous projects deeply involving Kubernetes and containerization of models
  • Developed against AWS and Azure services on occasion and deployed on the same
  • Incorporated local data caches for pre-population of features and stateful model support  
  • Experience with one or more popular machine learning frameworks and workbench products
  • A willingness to adapt, are passionate about accelerating model lifecycles, and capable of working independently, putting in extra effort when necessary, as we are an early stage startup


Our benefits include: 

  • Medical/dental/vision coverage
  • 401k
  • Lunch provided daily (and dinner when required!)
  • Abundant snacks and drinks 
  • Dedicated, heavily discounted parking and Clipper Direct
  • Gym reimbursement
  • Weekly happy hours and monthly company outings
  • $10k referral bonuses, because after we hire you, we’d love to hire some of your friends!


We are an equal opportunity employer and value diversity very highly at our company.  For us, diversity is the true key to innovation and everyone in the Datatron family is equally embraced for their unique perspective and experiences.  We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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