- Страна
- США
- Зарплата
- 188 600 $ – 330 000 $
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Scientist / Senior Scientist, Multimodal AI
Исключительно привлекательная вакансия в одном из самых амбициозных и хорошо финансируемых биотех-стартапов мира с очень высокой заработной платой и социально значимой миссией.
Сложность вакансии
Высокая сложность обусловлена требованием степени PhD, наличием публикаций в топовых конференциях (NeurIPS, CVPR) и необходимостью глубоких знаний как в Computer Vision, так и в распределенном обучении моделей на петабайтных данных.
Анализ зарплаты
Предлагаемая зарплата ($188k - $330k) находится на верхнем пределе рыночных значений для AI Scientist в США, особенно учитывая специфику Biotech, где компенсации часто превышают средние показатели по IT-сектору.
Сопроводительное письмо
I am writing to express my strong interest in the Scientist / Senior Scientist, Multimodal AI position at Altos Labs. With a PhD in Computer Science and extensive experience in building large-scale foundation models, I am particularly drawn to your mission of restoring cell health through cell rejuvenation. My background in developing Vision Transformers and implementing self-supervised learning aligns perfectly with your goal of unifying high-dimensional biomedical imaging with molecular data.
In my previous work, I have successfully managed high-performance ML pipelines and distributed training using PyTorch and DeepSpeed. I am excited by the challenge of implementing cross-domain mapping to synchronize heterogeneous biological datasets. My track record of technical contributions in venues like NeurIPS and CVPR demonstrates my commitment to scientific excellence and my ability to translate complex biological problems into performant, scalable code.
I am eager to bring my expertise in multimodal fusion and distributed cloud infrastructure to the Institute of Computation at Altos Labs. I look forward to the possibility of discussing how my technical skills and passion for biotechnology can contribute to your world-class AI ecosystem.
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Присоединяйтесь к Altos Labs, чтобы создавать ИИ-модели нового поколения для омоложения клеток и борьбы с возрастными заболеваниями!
Описание вакансии
Our Mission
Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.
For more information, see our website at altoslabs.com.
Our Value
Our Single Altos Value: Everyone Owns Achieving Our Inspiring Mission.
Diversity at Altos
Altos Labs has been named one of the Top 3 Biotech Companies and ranked for the second year on the Forbes 2026 Best Startups in America list. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.
What You Will Contribute To Altos
Altos Labs is building a world-class AI ecosystem to solve the most complex problems in human biology. You will directly design and build high-performance, scalable solutions that unify high-dimensional biomedical imaging with molecular and language data.
By implementing large-scale multimodal data fusion, you will move beyond simple image analysis to create predictive models that map across biological domains. You will be hands-on with the data and the code, collaborating with our engineering team to ensure these models are scalable, efficiently trainable on distributed cloud infrastructure, and accessible to our global research community.
Responsibilities
- Model Development: Design, code, and train large-scale foundation models (e.g., Vision Transformers, Multimodal LLMs) that can embed spatial data and integrate multiple modalities.
- Hands-on Data Fusion: Implement innovative cross-domain mapping and fusion strategies to synchronize heterogeneous biological datasets.
- Scaling & Training: Build and manage high-performance ML pipelines capable of processing petabyte-scale image repositories and multi-omics streams in a cloud environment.
- Technical Collaboration: Work directly in the trenches with experimental scientists and software engineers to translate biological complexity into performant code and reliable distributed systems.
Who You Are
We are looking for a technical specialist who thrives on solving "unsolvable" problems through code and rigorous experimentation. We are open to candidates at the Scientist I, Scientist II, or Senior Scientist level based on technical expertise.
Minimum Qualifications
- Education: PhD in Computer Science, AI/ML, Biomedical Engineering, or a related quantitative field.
- Hands-on CV Expertise: Deep experience building and deploying modern Computer Vision architectures (Vision Transformers, U-Nets, Self-Supervised Learning).
- Distributed Training: Proven experience training and fine-tuning large models at scale using frameworks like PyTorch Distributed, DeepSpeed, or Jax.
- Programming Mastery: Expert-level Python skills, with a focus on building production-ready machine learning code and large-scale data management systems.
- Scientific Contributions: A track record of technical contributions via high-impact publications (CVPR, ICCV, NeurIPS, etc.) or significant contributions to open-source ML frameworks.
Preferred Qualifications
- Direct experience with Multimodal Fusion (e.g., aligning image embeddings with transcriptomic or proteomic data).
- Proficiency with cloud-native AI tools (AWS/GCP, Kubernetes, Docker) and building automated MLOps workflows.
- Experience handling the unique noise and sparsity of biological data.
The salary range for Redwood City, CA:
- Scientist I, Machine Learning: $211,200 - $257,500
- Scientist II, Machine Learning: $237,800 - $290,000
- Senior Scientist I, Machine Learning: $270,600 - $330,000
The salary range for San Diego, CA:
- Scientist I, Machine Learning: $188,600 - $230,000
- Scientist II, Machine Learning: $223,900 - $273,300
- Senior Scientist I, Machine Learning: $251,700 - $307,000
#LI-NN1
Exact compensation may vary based on skills, experience, and location.
For UK applicants, before submitting your application:
- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.
Equal Opportunity Employment
We value collaboration and scientific excellence.
We believe that diverse perspectives and a culture of belonging are foundational to scientific innovation and inquiry. At Altos Labs, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining an inclusive environment.
Altos Labs provides equal employment opportunities to all employees and applicants for employment, without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Altos prohibits unlawful discrimination and harassment. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.
Note: Altos Labs will not ask you to download a messaging app for an interview or outlay your own money to get started as an employee. If this sounds like your interaction with people claiming to be with Altos, it is not legitimate and has nothing to do with Altos. Learn more about a common job scam at https://www.linkedin.com/pulse/how-spot-avoid-online-job-scams-biron-clark/
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- AWS
- Python
- PyTorch
- Large Language Models
- Kubernetes
- JAX
- Computer Vision
- MLOps
- Google Cloud Platform
- Docker
- Distributed Training
- DeepSpeed
- Self-Supervised Learning
- Vision Transformer
- Multimodal AI
Возможные вопросы на собеседовании
Вакансия требует опыта работы с мультимодальными данными. Важно понять, как кандидат решает проблему несовпадения размерностей и природы данных.
Опишите ваш опыт проектирования стратегий слияния (fusion) для разнородных данных, например, изображений и текстовых/молекулярных описаний. С какими основными трудностями вы сталкивались?
Работа предполагает обучение моделей на огромных массивах данных в облаке.
Какие техники оптимизации распределенного обучения (например, ZeRO, Pipeline Parallelism) вы использовали для обучения моделей, которые не помещаются в память одной GPU?
Биологические данные часто зашумлены и неполны.
Как вы подходите к проблеме разреженности (sparsity) и высокого уровня шума в специфических биологических датасетах при обучении Vision Transformers?
Позиция требует навыков написания production-ready кода.
Расскажите о вашем опыте построения MLOps-пайплайнов для автоматизации обучения и деплоя моделей в облачной среде (AWS/GCP).
Altos Labs ценит междисциплинарное сотрудничество.
Приведите пример, когда вам приходилось переводить сложную биологическую или научную задачу на язык алгоритмов и кода в сотрудничестве с учеными-экспериментаторами.
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- Страна
- США
- Зарплата
- 188 600 $ – 330 000 $