AI Systems Engineer
2 weeks ago
Abridge, established with a vision to enhance comprehension in healthcare, is seeking a talented individual to join our innovative team. Our AI-driven platform is designed to streamline medical dialogues, enhancing clinical documentation efficiency while allowing healthcare professionals to prioritize patient care.
Our advanced technology converts patient-clinician discussions into structured clinical notes instantaneously, featuring robust EMR integrations. Leveraging Linked Evidence and our specialized, auditable AI, we uniquely align AI-generated summaries with verified data, enabling providers to swiftly trust and validate the results. As leaders in generative AI for healthcare, we are setting benchmarks for the ethical application of AI across healthcare systems.
Position Responsibilities- Design, develop, and implement high-caliber machine learning software applications, infrastructure, and tools.
- Oversee technical domains from problem identification and requirements gathering to implementation and ongoing maintenance.
- Collaborate with machine learning researchers and engineers to execute and deploy algorithms, including machine learning models.
- Engage with stakeholders across machine learning and operational teams to refine systems design and execution.
- Create reusable software and systems to expedite development processes.
- Analyze, optimize, and troubleshoot system performance and resolve production issues.
- Develop systems with a focus on fault tolerance, scalability, security, and continuous enhancement.
- Minimum of 5 years of professional software development experience, with expertise in design patterns, data structures, and test-driven development.
- Bachelor's Degree or higher in Computer Science/Engineering, Statistics, Mathematics, or a related field.
- Proficient in creating production-quality software using languages such as C++, Python, or Java.
- Familiar with standard software engineering practices for the complete software lifecycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Experience with cloud environments, Kubernetes or Docker, and Infrastructure as Code (e.g., Terraform).
- Background in software design and architecture for highly available machine learning systems, including use cases for inference, evaluation, and experimentation.
- Strong understanding of low-level operating system concepts, including multi-threading, memory management, networking, storage, performance, and scalability.
- Excellent communication skills, both written and interpersonal.
- Experience in relevant technical fields such as natural language processing, machine learning, distributed systems, or infrastructure development for engineering/science users.
- Expertise in machine learning frameworks and methodologies, such as Pytorch or Tensorflow.
- Proven experience in incubating and deploying new technologies, collaborating closely with research scientists and technical teams from concept to implementation.
We appreciate individuals eager to learn and grow, and we recognize that exceptional team members may not fit every aspect of a job description. If you are interested in this opportunity but unsure of your fit, we encourage you to reach out.
Work Environment
We are looking for candidates who are open to a hybrid work model, with a commitment to working in the office multiple times a week.
Compensation
The salary range for this position is between $200K and $265K.
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