Machine Learning Systems Engineer (Staff/Senior)

Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.

Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.

We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense.

The Role

From transcribing medical parts of the conversation to delivering key takeaways, our trailblazing work in machine learning research makes the Abridge experience possible. We're currently looking to add a machine learning engineer to our team to help us build and release more machine learning-powered value to our users. 

What You'll Do

• Architect, design, and implement high-quality machine learning software applications, infrastructure, and tools.

• Lead technical domains starting from the problem definition and technical requirements along with implementation and maintenance

• Collaborate with machine learning researchers and engineers to implement and deploy algorithms, such as machine learning models.

• Work with stakeholders across machine learning and operations teams to iterate on systems design and implementation.

• Create re-usable software and systems to accelerate development.

• Profile, tune, and optimize system performance and debug production issues.

• Design systems for fault tolerance, scalability, security and continuous improvement.

What You'll Bring

• 5+ years of industry software development experience, with a background in design patterns, data structures, and test-driven development.

• Bachelor's Degree or greater in Computer Science/Engineering, Statistics, Mathematics, or equivalent.

• Proficient in developing production-quality software in languages such as C++, Python, or Java.

• Proficient with professional software engineering practices & standard practices for the full software life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.

• Experience with cloud based environments, Kubernetes or Docker, and Infrastructure as Code (Terraform, etc.)

• Experience in software design and architecture for highly available machine learning systems for use cases like inference, evaluation and experimentation.

• Excellent understanding of low level operating systems concepts including multi-threading, memory management, networking and storage, performance, and scale

• Excellent interpersonal and written communication skills

Ideally, You Have

• Experience in one or more relevant technical areas: natural language processing, machine learning, distributed systems, or building infrastructure for engineering/science users.

• Expertise in machine learning toolchains and techniques, such as Pytorch or Tensorflow.

• Demonstrated experience incubating and productionizing new technology, working closely with research scientists and technical teams from idea generation through implementation.

We value people who want to learn new things, and we know that great team members might not perfectly match a job description. If you’re interested in the role but aren’t sure whether or not you’re a good fit, we’d still like to hear from you.

Must be willing to work from our SF or NYC office 2-3x/week

We are actively seeking candidates based in or willing to relocate to the San Francisco Bay Area and/or the New York Tri-State area. This position requires a commitment to a hybrid work model, with the expectation of coming into the office 2-3 times per week.

Must be willing to travel up to 10%

Abridge typically hosts a 3 day builder team retreat every 3-6 months. These retreats often feature internal hackathons, collaborative project sessions, and social events that provide the team with opportunities to connect.

Why Work at Abridge?

• Be a part of a trailblazing, mission driven organization that uses audio as the wedge to improve the healthcare delive