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Senior Machine Learning Engineer - Speech to Text

Оценка ИИ

Исключительно привлекательная вакансия: работа в топовом стартапе с инвестициями $70M, сильная инженерная культура, участие мировых экспертов (Ян Лекун) и социально значимый продукт. Высокий потенциал профессионального роста.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубокой экспертизы в узкой нише Voice AI (ASR, диаризация, VAD) и опыта работы с высоконагруженными системами реального времени. Высокая планка задается сильной командой выходцев из Meta AI и сложностью медицинского домена.

Анализ зарплаты

Медиана95 000 €
Рынок80 000 € – 120 000 €
Оценка ИИ

Зарплата в объявлении не указана, но для позиции Senior ML Engineer в Париже в успешном стартапе серии C рыночные показатели составляют €80,000–€110,000 плюс опционы. Предложение Nabla, вероятно, находится в верхней границе рынка или выше, учитывая сложность задач и уровень команды.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Machine Learning Engineer position at Nabla. With over five years of experience in speech and audio ML, I have closely followed Nabla's impressive growth and its mission to restore the human connection in healthcare. My background in optimizing ASR and diarization systems for real-time production environments aligns perfectly with your current focus on scaling the clinical audio stack.

In my previous roles, I have successfully deployed transformer-based speech models and tackled challenges similar to those mentioned in the job description, such as improving robustness in noisy environments and optimizing streaming pipelines for low latency. I am particularly excited about the opportunity to work under the guidance of industry leaders like Yann LeCun and contribute to a product that processes billions of tokens to support tens of thousands of clinicians.

I am confident that my technical expertise in Python and speech architectures, combined with my product-oriented mindset, will allow me to make immediate contributions to your Voice AI squad. I look forward to the possibility of discussing how my skills can help Nabla continue to push the frontier of clinical AI.

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Откликнитесь в nabla уже сейчас

Присоединяйтесь к команде экспертов из Meta AI и создавайте будущее медицинского ИИ в Nabla!

Описание вакансии

About Nabla

We are a team of entrepreneurs, clinicians and engineers committed to bringing back joy to the practice of medicine.

Together with a community of clinician innovators, we’ve harnessed the best of machine learning science to develop Nabla: the leading AI assistant that’s restoring the human connection at the heart of healthcare. By streamlining clinical documentation, Nabla is helping clinicians focus on what matters most - patient care. Today, over 85,000 clinicians across 130+ healthcare organizations trust Nabla to support how they deliver care every day.

We’re at the start of an ambitious journey: Ambient listening, dictation, coding, and command capabilities are all converging into a proactive assistant that intuitively streamlines clinical and financial workflows.

Backed by a recent $70M Series C, we’re hiring to build the next generation of clinical AI and improve the lives of clinicians and patients everywhere.

This is a great time to join us!

The best of AI at the service of healthcare

Nabla’s phenomenal traction is the result of years of rigorous product and ML development.

Led by former Meta AI Research engineers, our team continuously pushes the frontier of speech and language AI in real-world clinical environments. We operate at scale, processing billions of tokens and thousands of hours of audio every week.

Yann LeCun, Meta’s Chief AI Scientist and Turing award winner, is an advisor to Nabla.

Engineering at Nabla

Engineering at Nabla is lean, fast-moving, and deeply technical. Our teams span machine learning, real-time audio processing, native desktop applications, and platform infrastructure to deliver AI into clinical settings reliably and at scale.

Your Team

Product development at Nabla is led jointly by Engineering and Product and organized into cross-functional squads. As a Senior ML Engineer specialized in Voice AI, you will join a squad focused on speech and ambient intelligence, contributing end-to-end to the evolution of our real-time clinical audio stack.

What you’ll do

As a Senior ML Engineer specialized in Voice AI, you’ll play a key role in shaping the intelligence layer that powers Nabla’s assistant. Voice is the foundation of our product, enabling clinicians to interact directly with Nabla and capturing everything that happens during medical encounters.

Working alongside experienced ML engineers already building our speech stack, you’ll significantly contribute to advancing the systems that transforms the >1M hours of raw clinical audio flowing through our systems every month into reliable, structured input for our AI assistant.

You will:

  • Contribute to the improvements of core components of our speech stack, including speech recognition, speaker diarization, voice activity detection (VAD), principal speaker detection, language detection and custom vocabulary.
  • Design and improve state-of-the-art speech systems, adapting modern architectures to real-world clinical environments (noisy rooms, overlapping speech, telehealth calls, and multilingual conversations).
  • Improve real-time performance, helping optimize streaming pipelines to balance latency, accuracy, and cost in live clinical workflows.
  • Increase robustness and reliability, ensuring consistent performance across accents, specialties, acoustic conditions, and healthcare organizations.
  • Strengthen our evaluation standards, defining and refining metrics around WER, DER, latency, multilingual performance, and production monitoring.
  • Contribute to the speech data strategy, improving dataset quality, annotation processes, and continuous learning loops from production feedback.
  • Collaborate closely with product, ML, and infrastructure engineers to ensure speech systems integrate seamlessly into downstream note generation and agentic workflows.

Your work will directly impact tens of thousands of clinicians. Improvements you help ship will be heard — literally — in live patient encounters every day.

Your DNA

We’re looking for a hands-on expert in speech and audio machine learning who combines research depth with production pragmatism.

Requirements:

  • Deep expertise in speech and audio ML systems (5+ years), including experience with ASR, diarization, VAD, or multilingual speech models.
  • Strong understanding of real-time or streaming ML systems, with experience optimizing for latency and reliability.
  • Experience working with transformer-based or hybrid speech architectures (e.g., wav2vec2, Whisper-like systems, conformers, etc.).
  • Solid knowledge of audio preprocessing, feature extraction, and robustness techniques.
  • Strong Python skills and experience deploying ML systems in production.
  • Ability to design and evaluate experiments with rigorous metrics tailored to speech systems (WER, DER, latency, robustness benchmarks).
  • Strong product mindset: you understand that improvements in speech quality directly impact clinician experience.
  • Fluent in English.

Nice to have:

  • Experience with multilingual speech systems and language detection.
  • Experience in healthcare or other high-reliability domains.
  • Experience working on edge or resource-constrained inference environments.

Life at Nabla

When you become a part of our company, you join a team of excellence-driven, curious, and genuinely kind individuals. Together, we're committed to making clinicians' lives easier and improving healthcare experiences for everyone. We believe in a world where clinicians can focus on what they were trained to do - caring for their patients, and where no patient feels their visit was rushed.

We come to work excited to leverage AI to do more for clinicians. We’re obsessed with our users’ satisfaction and we actively seek out opportunities to engage one-on-one with clinicians to understand how Nabla can better help. We consistently look for ways to improve and do not shy away from doing the work to excel. Whether it’s a feature our users asked for, or a new article for our blog, we prioritize collaboration to deliver exceptional outcomes.

We love having fun as much as we love work. Our #nablabla channel is as active as our #feature-show-off channel, we exercise during the work day at least 3 times a week (yoga, running, pilates, or HIIT, your choice!), enjoy regular off-sites to gather the team, and travel to see each other in places like NY, Paris, San Francisco, and many other vibrant cities. Oh, and we’re constantly snacking on chocolate or nuts!

If this sounds like an environment you’ll thrive in, we look forward to reading your application!

Our Values at Nabla

Joining Nabla means being part of a team that shares a commitment to excellence, humility, growth, and inclusion.

Every day is a new chance to excel

We aim for nothing less than the best and are willing to put in the effort and dedication required to exceed standards. We learn from yesterday’s failures and do better every day.

Stay humble

There’s no place for ego in our team. Our collective success is more important than individual achievements. We see humility as wisdom — keeping focus on the bigger picture.

Feedback is a gift

We embrace feedback and foster a culture of trust and respect that helps everyone grow. We communicate openly about both achievements and challenges, and we actively involve each other in finding solutions.

Committed to diversity

We recognize the ongoing challenge of diversity in tech. Our responsibility starts with fostering an inclusive environment where everyone feels empowered to be their authentic selves and do their best work.

Diversity & Inclusion

Diversity and inclusivity are fundamental values at Nabla. We embrace individuals from various backgrounds, including race, gender, educational history, sexual orientation, and beyond.

As an equal opportunity employer, we actively seek out and welcome applicants from diverse backgrounds, believing that a wide range of perspectives enriches our team and enhances our ability to innovate and thrive.

Avoid recruitment scams: Stay safe and informed

There is an active employment scam which is now using Nabla to collect personal information or financial scams. If you’re contacted by a Nabla recruiter, please ensure whomever is contacting you truly represents Nabla and is utilizing a nabla.com email address. We will never ask for the exchange of any money or credit card details during the recruitment process. Nabla utilizes a hiring platform for all applications; please be aware of any suspicious email activity from people who could be pretending to be recruiters or senior professionals at Nabla. You can find more information following this link.

Nabla does not accept unsolicited CVs from recruiters or employment agencies in response to the Nabla Careers page or a Nabla social media post. Any unsolicited CVs, including those submitted directly to hiring managers, are deemed to be the property of Nabla.

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Навыки

  • Python
  • Machine Learning
  • Transformers
  • Speech Recognition
  • Audio Processing
  • ASR
  • Feature Extraction
  • Whisper
  • Diarization
  • Streaming Systems
  • Voice Activity Detection
  • Wav2vec2
  • Conformer

Возможные вопросы на собеседовании

Проверка понимания специфики медицинского домена (шум, наложение голосов, терминология).

Как бы вы адаптировали стандартную модель Whisper для работы в условиях шумного медицинского кабинета с частым перекрытием голосов врача и пациента?

Оценка навыков оптимизации для реального времени.

Какие стратегии вы используете для минимизации задержки (latency) в потоковых (streaming) системах распознавания речи без значительной потери точности?

Проверка опыта работы с метриками.

Помимо WER и DER, какие специфические метрики вы бы внедрили для оценки качества транскрибации многоязычных медицинских консультаций?

Оценка навыков работы с данными.

Как выстроить эффективный цикл дообучения (continuous learning loop), используя обратную связь от врачей о фактических ошибках в транскриптах?

Проверка технических знаний архитектур.

В чем основные преимущества и недостатки использования гибридных архитектур (например, Conformer) по сравнению с чисто трансформерными моделями в задачах Voice AI?

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