- Страна
- США
- Зарплата
- 251 700 $ – 330 000 $
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на вакансии с ИИ

Senior Machine Learning Scientist, AI Agents
Исключительная вакансия в одной из самых амбициозных и хорошо финансируемых биотех-компаний мира. Высокая зарплата, работа с передовыми технологиями (Agentic AI) и благородная миссия делают это предложение топовым на рынке.
Сложность вакансии
Высокая сложность обусловлена требованием степени PhD, глубокой экспертизы в узкой области Agentic AI и одновременно серьезных знаний в биоинформатике. Позиция предполагает работу на стыке передовых технологий ИИ и фундаментальной науки.
Анализ зарплаты
Предлагаемая зарплата ($251k - $330k) находится на верхнем пределе рыночных значений для Senior ML ролей в США, особенно учитывая специфику Biotech сектора. Это значительно выше среднего уровня по рынку для аналогичного опыта в общих технологических компаниях.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Machine Learning Scientist position at Altos Labs. With a PhD and extensive experience in developing agentic AI systems, I am particularly drawn to your mission of restoring cell health through rejuvenation. My background in bioinformatics, combined with hands-on expertise in LangGraph, RAG architectures, and LLM-based tool use, aligns perfectly with your goal of building computational platforms for biological data curation.
In my previous work, I have successfully implemented production-quality agentic workflows and context engineering techniques that bridge the gap between complex data and actionable scientific insights. I am impressed by Altos Labs' commitment to scientific excellence and its recognition as a top biotech startup. I am eager to bring my skills in prompt optimization and AI-assisted development to the Institute of Computation to help accelerate clinical R&D and the discovery of novel interventions.
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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
As part of our team, you will help to accelerate and optimize our progress in agentic AI methods for biological and clinical data curation and analysis.
In this role, you will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. You will collaborate with biomedical research experts as well as other machine learning scientists and engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem, focusing on designing and building state-of-the-art agentic AI systems and workflows that tackle biological questions, accelerate clinical data analysis, and aid in the discovery of novel interventions for aging and disease.
The successful candidate will combine deep expertise in agentic AI methods with a strong foundation in bioinformatics and/or clinical R&D. You will work closely with domain experts to translate complex biological and clinical data challenges into intelligent, automated solutions. You will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.
Responsibilities
- Design and develop agentic AI workflows for biological and clinical data curation tasks
- Research and implement advanced context engineering techniques (RAG, agentic RAG, graph RAG) tailored to biomedical data
- Develop and optimize prompts and agent architectures for reliability, accuracy, and scientific rigor
- Build LLM-based tool-use systems and integrations relevant to bioinformatics and clinical R&D pipelines
- Collaborate with bioinformatics scientists, clinical researchers, and domain experts to identify automation opportunities and translate them into agentic solutions
- Evaluate and benchmark agentic systems, establishing rigorous metrics for performance and correctness in scientific contexts
- Stay current with the rapidly evolving landscape of agentic AI methods and contribute to internal best practices
Who You Are
- Proven track record leveraging machine learning and AI to solve real-world problems
- Expertise in agentic AI methods development, including prompt optimization, LLM-based tool use, context engineering (RAG, agentic RAG, graph RAG), and agent evaluation
- Experience writing production-quality code with agentic frameworks (e.g., LangGraph, Pydantic-AI, DSPy, or similar)
- Deep familiarity with bioinformatics and/or clinical R&D, with the ability to engage meaningfully with domain experts on biological and clinical questions
- Proficiency with AI-assisted development tools (e.g., Claude Code, Cursor) to iterate rapidly
- A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focused on professional growth
- Able to advise others across the wider function / company on cutting edge agentic AI practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, machine learning, and medicine
- Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
Minimum Qualifications
- PhD in Computer Science, Machine Learning, Bioinformatics, or a related field
- Demonstrated experience developing agentic AI systems, including LLM-based tool use, prompt engineering, and context engineering techniques
- Strong foundation in machine learning principles and their application to real-world problems
- Strong background in bioinformatics, computational biology, or clinical R&D
- Familiarity with MCP server development and agent skill creation
- Very strong programming skills in Python, with experience writing production-quality, well-documented code
- Strong track record of published peer-reviewed research in AI/ML and/or computational biology
Preferred Qualifications
- Experience with AWS services (S3, Bedrock, Lambda) in the context of AI/ML workflows
- Experience with clinical trial data, regulatory data curation, or biomedical ontologies (e.g., CDISC, SNOMED, MedDRA)
- Track record working with NGS data (e.g., RNA-seq, ATAC-seq, DNA methylation) or other biological data modalities
- Experience designing evaluation frameworks and benchmarks for agentic AI systems
- Familiarity with knowledge graph construction and graph-based retrieval methods
The salary range for Redwood City:
- Senior Scientist I, Machine Learning: $270,600 - $330,000
The salary range for San Diego:
- Senior Scientist I, Machine Learning: $251,700 - $307,000
Exact compensation may vary based on skills, experience, and location.
#LI-NN1
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
- Python
- Machine Learning
- Bioinformatics
- Large Language Models
- RAG
- LangGraph
- DSPy
- AWS
- S3
- Bedrock
- Lambda
- Computational Biology
- Prompt Engineering
Возможные вопросы на собеседовании
Проверка практического опыта работы с современными фреймворками для создания ИИ-агентов.
Расскажите о вашем опыте использования LangGraph или DSPy для создания сложных многошаговых агентов. С какими основными трудностями вы столкнулись при обеспечении надежности их работы?
Оценка навыков работы с контекстом в специфической научной области.
Как бы вы спроектировали систему Graph RAG для работы с биомедицинскими онтологиями и научными публикациями, чтобы минимизировать галлюцинации модели?
Проверка способности применять ИИ к специфическим биологическим данным.
Каким образом агентные системы могут ускорить анализ данных секвенирования (например, RNA-seq) по сравнению с традиционными биоинформатическими пайплайнами?
Оценка методологии тестирования ИИ-систем в критически важных областях.
Какие метрики и фреймворки оценки вы считаете наиболее подходящими для проверки корректности выводов ИИ-агента в контексте клинических исследований?
Проверка навыков командного взаимодействия в междисциплинарной среде.
Опишите случай, когда вам нужно было объяснить сложную концепцию машинного обучения эксперту в области биологии. Как вы адаптировали свой подход?
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- Страна
- США
- Зарплата
- 251 700 $ – 330 000 $