Machine Learning Engineer

Company: Machinify, Inc.
Location: Palo Alto, California, United States
Type: Full-time
Posted: 26.JUL.2021

Summary

Remote Position About Machinify: There are few institutions that have a bigger impact on peoples' lives than the healthcare system; not ...

Description

Remote Position


About Machinify:

There are few institutions that have a bigger impact on peoples' lives than the

healthcare system; not only is it 20% of the U.S. economy, but it is often literally a matter of life and death. There is little disagreement that the U.S. healthcare system can function better - delivering better outcomes for less money. While there is also little consensus about how to fix it, it's clear that technology will have to play a major role. Enter Machinify.

At Machinify, we are methodically reinventing how healthcare is delivered. Specifically, we are developing AI-powered data products that reimagine healthcare administration in a manner that dramatically improves efficiency, eliminates error and waste, and perhaps most importantly truly bends the cost curve. Our customers are some of the largest and most powerful healthcare institutions in the country.

Until now, the ability to develop complex, AI-powered software has been the province of a few tech giants, with legacy industries left out in the cold. Machinify brings this power to the healthcare industry in a simple, easy-to-implement way.

Machinify's leadership team has previously built numerous industry-changing companies in the mobile, video and customer electronics space, but Machinify is poised to have a greater impact than all of our previous companies combined. After just a short time in-market, we already have several industry-leading customers, with millions of dollars in annual recurring revenue. The company has received funding from Battery Ventures, GV, and Matrix Partners, three of the world's leading VC firms.


What You'll Do:

Machinify is seeking a ML Data Engineering to own our data ingestion and transformation process in support of our Data Science team, you will:

  • Work with a cross-functional organization including engineering, delivering, subject-matter experts, product managers, as well as platform engineers to deliver a scalable framework.
  • Map the customer data into Machinify canonical form. Identify and ingest non canonical fields and generalize the process to a minimal level of customization.
  • Ultimately own the data and make them available within the Data Science organization as needed.

Skills We Are Looking For:

We are a startup and expect each team member to move fast, take initiative, and spot and solve problems. You can expect the same from us.


Key skills and minimum qualifications include:

  • 7+ years experience as hands-on ML Data Engineering in either as a lead developer or in a management role. SQL proficiency is a must.
  • 5+ years of experience managing the delivery of complex data
  • Experience with cloud-based services and enterprise software environments.
  • Strong data technical background as evidenced by prior experience as a hands-on
  • Familiarity with frameworks and protocols for data transfer, data consumption and data manipulation
  • Analytical approaches to problem solving and data-driven decision making.
  • Ability to balance trade-offs among multiple competing priorities.


Preferred Qualifications:

  • Masters in Computer Science or STEM disciplines
  • Experience with ML pipelines, and Big Data. Plus if the candidate has worked with medical records
  • Startup experience

What It's Like to Work Here:


The best companies are those that put talented people in a position where they can do their best work, challenge themselves, develop and grow, and make important contributions to the success of the company. Machinify is just this place. Specifically:

  • The customer is at the center of everything we do. We employ innovative thinking to solve problems they don't know they have yet.
  • Everyone has a voice. Decisions are based on who makes the best argument vs who has the biggest title.
  • We encourage personal responsibility and flexibility over defined rules and practices, and impact over process.
  • We are a team of diverse backgrounds and perspectives but a common focus on the customer.
  • You'll be trusted to make big decisions on your own but with the proper support. We make decisions quickly without being rash.
  • We understand that things sometimes go wrong. Our team members hold themselves accountable for their performance, but also see every setback or mistake as a learning opportunity.

 
Apply Now

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