MLOps Engineer

Lviv, Ukraine
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You will join a high-growth, high-powered GTM Data team of Analytic Engineers, Data Scientists, Data Engineers, and ML Engineers that deeply value intellectual curiosity, collaboration, and autonomy. The algorithms, insights, and Data products we develop allow our Sales and CS reps to support our prospects and customers more effectively. We have big plans and invite talented, passionate engineers to help us achieve them! HubSpot is early in its GTM AI maturity curve, which provides a unique opportunity for enormous impact.

Responsibilities

  • Work closely with both Software and Machine Learning Engineers to create an exceptional developer experience by setting up automation and CI / CD pipelines
  • Work with Data Scientists and ML Engineers to facilitate a smooth transition from model development to model hosting by the MLOps team by jointly agreeing on a set of build artifacts, testing, and documentation required for effective deployment.
  • Carry out software integration work to connect models hosted by the MLOps team to other systems at HubSpot so the insights and recommendations can be used effectively
  • Support best-in-class set of open-source Machine Learning tools to increase team productivity
  • Monitor application performance, diagnose bottlenecks, and implement performance improvements as needed
  • Respond to incidents and outages. Perform root cause analysis and work with the team to implement practices to prevent the recurrence of the issue. 
  • Participate in code and design reviews

Required skills

  • Degree in Computer Science, Software Engineering or related field
  • 5+ years experience in Software Engineering with experience supporting high-availability applications
  • Experience working with Docker, Kubernetes and Helm to deploy applications and distributed systems
  • Excellent Python or Java programming skills
  • Experience creating custom CI/CD pipelines (e.g. GitHub Actions, Jenkins, etc.)
  • Strong understanding of RESTful API design principles and best practices
  • Experience designing robust systems and monitoring strategies to ensure high levels of quality and availability, preferably in the context of AI/ML workloads
  • Able to communicate highly technical concepts to lead effective design conversations
  • Curious, creative, collaborative problem solver with experience delivering iterative solutions to difficult problems

As a plus

  • Software Reliability Engineering experience
  • Prior experience in a Machine Learning operations team with ML/AI techniques and their applications

We offer

  • Professional development support (books, online courses, conferences, certifications, English classes, and clubs)
  • Work in a comfortable office (no open space policy, nice relax/sports areas, spaciously bar/kitchen, shower, mini-laundry)
  • Free lunches
  • Flexible working hours and WFH policy (upon agreement with the teammates)
  • Home office setup compensation
  • Medical insurance or sports compensation
  • Competitive salary for all team members
  • 20 business days of paid vacation, additional vacation in case of baby birth
  • Sick leaves compensation
  • Maternity/paternity leave
  • Corporate events and team-buildings