Machine Learning Scientist, ASR (All Levels)
Company: Abridge
Location: San Francisco
Posted on: May 19, 2025
Job Description:
About AbridgeAbridge 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. We have
offices located in the SoHo neighborhood of New York, the Mission
District in San Francisco, and Lawrenceville in Pittsburgh.The
RoleFrom 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 for a research scientist with experience in speech
recognition to help us improve the performance and robustness of
our transcription modules.The ideal candidate will bring technical
mastery, fluency with foundation models, speech recognition,
genuine interest in the medical domain, and strong critical
thinking skills to the role. At Abridge, all of our ML work has a
strong research component, and all of our research scientists
contribute directly to real products that impact the lives of
doctors.What You'll Do
- Advance the state of the art in medical ASR, in areas including
accurate transcription of clinical conversations, support of a wide
variety of languages and dialects, speaker diarization,
domain-specific language modeling, robust handling of diverse
accents and noise conditions, and development of novel evaluation
and experimentation techniques.
- Actively contribute to the wider research community by sharing
and publishing original research
- Research and implement algorithms and methods for long-form and
real-time speech recognition
- Perform data preprocessing and define performance measures
based on development and test sets
- Implement and improve tools, algorithms, and prototypes
- Be responsible for measuring and optimizing the quality of your
algorithms
- Help to define important problems, identify appropriate
baselines, develop state-of-the-art methods, and ship them into
production
- Dial deeply into real-time feedback from clinicians to guide
further refinements and innovations
- Be results-oriented in the face of ambiguous problems and
uncertain outcomesWhat You'll Bring
- 2+ years experience in building speech recognition systems
- Strong research background, as demonstrated through papers and
a graduate degree (MS or PhD) in Electrical Engineering, Computer
Sciences, Mathematics, or equivalent experience with a
specialization in speech recognition or machine learning
- High-impact publications at peer-reviewed speech conferences
(e.g. ICASSP, Interspeech, SLT) or NLP/ML conferences (NAACL, ACL,
NeurIPS, ICML, ICLR)
- Significant real-world impact, as demonstrated through
open-source contributions and deployed technology
- Strong programming skills with proven experience crafting,
prototyping, and delivering machine learning solutions into
production
- Experience with deep learning libraries (e.g. PyTorch, Jax,
Tensorflow) and platforms, multi-GPU training, and statistical
analyses of observational and experimental data
- Deep knowledge of ASR technologies such as acoustic modeling,
language modeling, neural networks, HMM, WFST, and feature
extraction
- Hands-on experience in ASR tool kits such as Sphinx, Kaldi,
HTK, or JuliusIdeally, You Have
- Research work or publications pertaining to applying deep
learning methods to speech recognition
- Deep fluency in academic fields relevant to speech
recognitionBase Salary: $200,000 USD - $300,000+ USD per year +
EquityThe salary range provided is based on transparent pay
guidelines and is an estimate for candidates residing in the San
Francisco and New York City metro areas. The actual base salary
will vary depending on the candidate's location, relevant
experience, skills, qualifications, and other job-related factors.
Additionally, this role may include the opportunity to participate
in a company stock option plan as part of the total compensation
package.Must be willing to work from our SF or NY office at least
3x per weekThis position requires a commitment to a hybrid work
model, with the expectation of coming into the office a minimum of
(3) three times per week. Relocation assistance is available for
candidates willing to move to San Francisco within 6 months of
accepting an offer.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.Why work at Abridge?At Abridge, we're driven by our mission to
bring understanding and follow-through to every medical
conversation. Our culture is founded on doing things the "inverse"
way in a legacy system-focusing on patients, instead of the system;
focusing on outcomes, instead of billing; and focusing on the
end-user experience, instead of a hospital administrator's
mandate.Abridgers are engineers, scientists, designers, and health
policy experts from a diverse set of backgrounds-an experiment in
alchemy that helps us transform an industry dominated by EHRs and
enterprise into a consumer-driven experience, one recording at a
time. We believe in strong ideas, loosely held, and place a high
premium on a growth mindset. We push each other to grow and expose
each other to the latest in our respective fields. Whether it's
holding a PhD-level deep dive into understanding fairness and
underlying bias in machine learning models, debating the merits of
a Scandinavian design philosophy in our UI/UX, or writing responses
for Medicare rules to influence U.S. health policy, we prioritize
sharing our findings across the team and helping each other be
successful.How we take care of Abridgers:
- Generous Time Off: 13 paid holidays, flexible PTO for salaried
employees, and accrued time off for hourly employees.
- Comprehensive Health Plans: Medical, Dental, and Vision plans
for all full-time employees. Abridge covers 100% of the premium for
you and 75% for dependents. If you choose a HSA-eligible plan,
Abridge also makes monthly contributions to your HSA.
- Paid Parental Leave: 16 weeks paid parental leave for all
full-time employees.
- 401k and Matching: Contribution matching to help invest in your
future.
- Pre-tax Benefits: Access to Flexible Spending Accounts (FSA)
and Commuter Benefits.
- Learning and Development Budget: Yearly contributions for
coaching, courses, workshops, conferences, and more.
- Sabbatical Leave: 30 days of paid Sabbatical Leave after 5
years of employment.
- Compensation and Equity: Competitive compensation and equity
grants for full time employees.
- ... and much more!Diversity & InclusionAbridge is an equal
opportunity employer. Diversity and inclusion is at the core of
what we do. We actively welcome applicants from all backgrounds
(including but not limited to race, gender, educational background,
and sexual orientation).Staying safe - Protect yourself from
recruitment fraudWe are aware of individuals and entities
fraudulently representing themselves as Abridge recruiters and/or
hiring managers. Abridge will never ask for financial information
or payment, or for personal information such as bank account number
or social security number during the job application or interview
process. Any emails from the Abridge recruiting team will come from
an @ email address. You can learn more about how to protect
yourself from these types of fraud by referring to . Please
exercise caution and cease communications if something feels
suspicious about your interactions.
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Keywords: Abridge, Union City , Machine Learning Scientist, ASR (All Levels), Accounting, Auditing , San Francisco, California
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