Machine Learning Systems Engineer (Staff/Senior)
Description For Machine Learning Systems 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 a Machine Learning Systems Engineer, you'll be at the forefront of scaling and deploying ML models that power this innovative healthcare solution. The role combines technical expertise in ML systems with practical implementation, requiring skills in Python, Kubernetes, and cloud infrastructure.
You'll be responsible for architecting and implementing ML software systems, ensuring they can handle increasing traffic demands while maintaining high availability and performance. The position offers a competitive salary range of $200K-$265K plus equity, along with comprehensive benefits including full medical coverage, learning budgets, and flexible PTO.
The ideal candidate brings 5+ years of ML model deployment experience, strong technical skills, and a passion for healthcare innovation. You'll work in a hybrid setting from the San Francisco office, collaborating with a diverse team of practitioners, scientists, and engineers. This is an opportunity to make a significant impact in healthcare while working with cutting-edge AI technology.
The company culture emphasizes growth, innovation, and a mission-driven approach to improving healthcare understanding. With a focus on patient-centric solutions and responsible AI deployment, Abridge offers a unique opportunity to work on meaningful problems while advancing your career in ML engineering.
Responsibilities For Machine Learning Systems 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 teams to ensure seamless integration of models with services
- Work with stakeholders to iterate on systems design and implementation
- Optimize and maintain the performance of ML systems
- Troubleshoot production issues and improve systems
Requirements For Machine Learning Systems 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
- Experience in software design for highly available machine learning systems
- Understanding of low-level operating systems concepts
- Bachelor's/Master's Degree in Computer Science/Engineering or related field
- Excellent interpersonal and written communication skills
Benefits For Machine Learning Systems Engineer (Staff/Senior)
- Flexible/Unlimited PTO plus 13 paid holidays
- Equity for all salaried team members
- 100% medical insurance premium coverage for employee, 75% for dependents
- 100% dental & vision insurance 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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