ML Infrastructure Engineer (Staff/Senior)
Description For ML Infrastructure Engineer (Staff/Senior)
Abridge, founded in 2018, is revolutionizing healthcare through their AI-powered platform that transforms medical conversations into structured clinical notes in real-time. As an ML Infrastructure Engineer, you'll be at the forefront of scaling and deploying machine learning models that power this innovative healthcare solution. The role combines technical expertise in ML systems with practical application in healthcare technology.
You'll be responsible for architecting and implementing scalable ML software systems, ensuring robust model deployment, and maintaining high-performance infrastructure. The position requires expertise in Python, Kubernetes, and cloud environments, with a focus on building fault-tolerant, highly available systems. You'll work closely with ML researchers and engineers to integrate models with various platforms and services.
The company offers an attractive compensation package including a competitive base salary range of $200K-$265K plus equity, comprehensive benefits, and a strong focus on work-life balance. The role is hybrid, requiring 3 days per week in the San Francisco office, with relocation assistance available.
Abridge's culture emphasizes innovation, growth, and collaboration, bringing together diverse expertise from engineering, science, design, and health policy. They're committed to transforming healthcare through technology while maintaining a strong focus on patient outcomes and user experience. The company provides numerous opportunities for professional development, including a generous learning budget and regular team retreats.
This is an excellent opportunity for an experienced ML engineer looking to make a meaningful impact in healthcare while working with cutting-edge AI technology in a supportive, mission-driven environment.
Responsibilities For ML Infrastructure Engineer (Staff/Senior)
- Architect, design, and implement ML software systems for deploying and managing models at scale
- Stand up ML models for inference and ensure they handle traffic increases
- Develop and maintain infrastructure that supports efficient ML operations
- Collaborate with ML researchers and engineers for seamless integration
- Optimize and maintain ML systems performance
- Troubleshoot production issues and improve systems
- Work with stakeholders to iterate on systems design and implementation
Requirements For ML Infrastructure Engineer (Staff/Senior)
- 5+ years of experience in ML model deployment and scaling
- Strong proficiency in Python and Kubernetes
- Expertise in designing fault-tolerant, highly available systems
- Experience with cloud environments and Infrastructure as Code
- Proficiency in optimizing system performance
- Bachelor's/Master's Degree in Computer Science/Engineering or related field
- Excellent interpersonal and written communication skills
- Must be willing to work from SF office at least 3x per week
- Must be willing to travel up to 10%
Benefits For ML Infrastructure Engineer (Staff/Senior)
- Flexible/Unlimited PTO plus 13 paid holidays
- Equity for all salaried team members
- 100% medical premium coverage for employee, 75% for dependents
- 100% dental & vision premium coverage for employee, 75% for dependents
- FSA & HSA Accounts
- $3,000 annual learning and development budget
- 401k Plan
- 16 weeks paid parental leave
- Flexible working hours
- $1,600 home office budget
- 30 days paid Sabbatical Leave after 5 years
- Relocation assistance available
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