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Machine Learning Engineer
Location
Remote
Employment Type
Full-Time
Department
AI & Machine Learning
Salary Range
Competitive, based on experience
Role Overview

Lokra is looking for a Machine Learning Engineer to develop and productionize useful, responsible AI capabilities for healthcare workflows. You will work with product, data, and engineering colleagues to move from problem definition and experimentation to evaluated, monitored solutions.

Responsibilities
  • Develop, evaluate, and iterate on machine learning or AI solutions for defined product needs
  • Prepare and assess data while documenting assumptions, limitations, and quality concerns
  • Build reliable pipelines and services for deploying and operating models
  • Measure model performance and monitor for quality, reliability, and unintended behavior
  • Collaborate with backend engineers to integrate models into production workflows
  • Communicate results and technical trade-offs to technical and non-technical stakeholders
What You'll Be Responsible For

Taking ML work from experimentation through testing, deployment, and monitoring Using appropriate evaluation methods and clearly reporting model limitations Contributing to responsible handling of data and AI in healthcare contexts

Requirements
  • 3+ years of experience in machine learning, applied AI, or a closely related engineering role
  • Strong programming skills in Python and experience with common ML tooling
  • Experience preparing data, training or adapting models, and evaluating results
  • Understanding of production ML concerns such as reproducibility, monitoring, and model drift
  • Ability to explain uncertainty, limitations, and technical findings clearly
  • Careful approach to privacy, safety, and responsible use of data
What We Offer
  • Meaningful work applying AI to real healthcare workflow challenges
  • Remote, collaborative working environment
  • Opportunity to shape the evaluation and deployment practices for AI features
  • Professional growth as the team and product evolve
Our Hiring Process
  • Application review
  • Introductory conversation
  • Machine learning technical discussion
  • Practical problem-solving or case discussion
  • Final interview with the team
  • Offer