Machine Learning Operations Engineer (MLOps)

Our client is on a mission to disrupt the healthcare industry by putting patients first. They are creating a platform that helps patients co...

Our client is on a mission to disrupt the healthcare industry by putting patients first. They are creating a platform that helps patients collect, organize, and share their medical records digitally. Anyone can use it to get a second opinion, coordinate with a caregiver, or donate to research. Their platform enables patients to get full access and control of their health data, allowing them to share it securely using blockchain based smart contracts with family, doctors and providers, and extracting the relevant clinical context from it using ML and NLP to enable faster diagnosis and treatment. They are well funded and have an all-star founding and current team, the founder's last company was sold to Apple and are currently backed by a strong investment team led by Andreessen Horowitz.

In this role, you will focus on designing and developing tools and capabilities to enable the Data Science and Clinical teams with data management and data annotation as well as architecting ML/AI solutions for productization. You will serve as a bridge between the Data Science, clinical, and engineering teams to lead efforts to transform ML POC functions to product-grade features. You will collaborate with data scientists, clinicians, and product managers to make informed decisions, manage risks, and create opportunities. You will demonstrate scaled ML Deployment and MLOps experience to address complex healthcare data problems!
Required Skills & Experience

• 4+ years of general software engineering
• Prior Data Engineering, turned ML SW engineer ideal fit
• Strong python development skills
• Proven ability to translate insights into product recommendations
• Design, develop and refine infrastructure for Clinical ML platform, enabling data annotation, rapid ML/AI model development, training, and evaluation at scale
• Establish ML engineering processes and best practices for data scientists utilizing our ML platform
• Experience working with unstructured data
• BS or MS in Computer Science or related field
• Experience using Java or deep learning frameworks is a bonus

What You Will Be Doing

Tech Breakdown

• 5% Maintenance, Testing, Debugging
• 95% New Development: Building, Training, and Deploying models in platform

Daily Responsibilities

• 70% Hands on
• 30% Team Collaboration

The Offer

• Competitive Salary: Up to $170,000k/year, DOE
• Equity

You will receive the following benefits:

• Equity/Stock Options
• Medical Insurance & Health Savings Account (HSA)
• 401(k)
• Paid Sick Time Leave
• Pre-tax Commuter Benefit
• Unlimited PTO
• Fun startup culture with secure backing
• Unlimited snacks and coffee along with catered lunches and happy hours

Applicants must be currently authorized to work in the United States on a full-time basis now and in the future.

This role does not offer sponsorship or c2c

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