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Software Engineer, ML Engineering/ML Ops

Remote, United States
$102,350 to $150,050 (for all locations outside San Francisco Bay Area) and $120,000 to $170,000 (for San Francisco Bay Area), cash bonus, and stock options
Software Development
Machine Learning
Python
AWS
Cloud Computing
Docker

We seek a highly motivated and dynamic Software Engineer to join our Machine Learning (ML) Engineering and MLOps team. This position is ideal for an engineer passionate about building and deploying scalable ML systems. The successful candidate will work closely with our experienced engineers to design, build, and maintain the infrastructure and tools necessary for rapid ML development and deployment. You will gain hands-on experience with the latest technologies in machine learning and cloud computing, contributing to projects that impact our products and services, and ultimately, move the needle on heart disease. #LI-Remote; #LI-IB1

Required Qualifications

  • Bachelor's/Masters degree in Computer Science, Engineering, Mathematics, or a related field
  • 2+ years of relevant experience
  • Experience developing distributed systems, big data technologies, and real-time data processing.
  • Familiarity with machine learning concepts and frameworks (e.g., PyTorch, Scikit-learn).
  • Strong foundation in software engineering principles and practices, with proficiency in at least one programming language (e.g., Python, C++).
  • Experience with cloud services (AWS, GCP, Azure) is a plus.
  • Understanding of data structures, algorithms, and software design principles.
  • Basic knowledge of containerization and orchestration technologies (e.g., Docker).
  • Strong problem-solving skills and the ability to work independently as well as collaboratively in a team environment.
  • Excellent communication and interpersonal skills.

How You Stand Out

  • Experience with continuous integration and continuous deployment (CI/CD) pipelines and familiarity with related tools (e.g., Jenkins, Github Actions).
  • Experience with a container orchestration framework (e.g., Kubernetes).
  • Experience with data warehouses (e.g., Redshift / Snowflake / Databricks).
  • A keen interest in staying up-to-date with the latest trends and advancements in machine learning, artificial intelligence, and cloud computing.
  • Demonstrated initiative and creativity in solving complex problems.
  • Blog (or other media) communicating the candidate’s data science or engineering projects, ideas, or first-principles thinking.

A reasonable estimate of the base salary compensation range is $102,350 to $150,050 (for all locations outside San Francisco Bay Area) and $120,000 to $170,000 (for San Francisco Bay Area), cash bonus, and stock options.

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