- Страна
- США
- Зарплата
- 117 000 $ – 150 000 $
Откликайтесь
на вакансии с ИИ

Applied Machine Learning Engineer
Отличная вакансия с четко определенным стеком технологий, прозрачным диапазоном зарплаты и социально значимой миссией в сфере здравоохранения. Гибридный формат работы и фокус на инновациях (AI-агенты, LLM) делают её очень привлекательной для опытных инженеров.
Сложность вакансии
Роль требует не только навыков программирования на Python, но и глубокого понимания математической статистики, причинно-следственного вывода (causal inference) и способности внедрять научные статьи в продакшн. Высокая планка ожиданий по работе с современным стеком (PyTorch, Snowflake, Docker) делает позицию сложной для новичков.
Анализ зарплаты
Предлагаемый диапазон $117,000–150,000 соответствует рыночным медианам для ML-инженеров в США, особенно в таких хабах, как Чикаго. Верхняя граница в $150k является конкурентной для уровня Middle/Senior в индустрии HealthTech.
Сопроводительное письмо
I am writing to express my strong interest in the Applied Machine Learning Engineer position at Strata. With a solid background in implementing machine learning models in Python and a deep interest in translating research papers into production-ready solutions, I am excited about the opportunity to contribute to your mission of improving healthcare through advanced analytics. My experience with PyTorch, causal inference, and optimization techniques aligns perfectly with the technical requirements of your AI and ML stack.
In my previous work, I have successfully bridged the gap between theoretical research and practical application, much like the 'Day in the Life' described in your posting. I am particularly drawn to Strata's focus on integrating generative AI and agentic workflows into a platform that supports over half of the nation’s leading healthcare providers. I am confident that my skills in statistical modeling and my passion for building mission-critical healthcare analytics will allow me to make a significant impact on your team.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в stratacareers уже сейчас
Присоединяйтесь к Strata, чтобы внедрять передовые AI-решения в здравоохранение и работать с новейшими исследованиями в области машинного обучения!
Описание вакансии
How You’ll Make an Impact
As an Applied Machine Learning Engineer, you will collaborate with architects, data scientists, agentic AI developers, platform engineers, and the product team to build advanced AI and ML capabilities into our platform. Your work will drive innovation in generative AI and beyond, integrating and customizing a wide range of machine learning techniques to solve complex problems in healthcare. By developing next-generation AI agents, algorithms, and computation engines, you will help Strata strengthen its market leadership, improve operational efficiency, and support healthcare providers in delivering high-quality care while maintaining financial health.
A Day in the Life
- Read and translate the latest research (e.g., arXiv papers) into production-ready solutions in Python.
- Prototype and iterate on machine learning models, focusing on areas such as regression, causal inference, optimization, and vector embeddings.
- Collaborate with cross-functional teams to embed ML and AI capabilities directly into our software platform.
- Partner with data scientists to design experiments and apply statistical concepts to real-world data.
- Optimize, test, and scale ML models to support mission-critical healthcare analytics.
Our Technology Stack
Our core platform is used by more than half of the nation’s leading healthcare providers, enabling them to leverage financial, operational, and clinical data. Our AI and ML stack includes:
- Languages & Libraries: Python, PyTorch, NumPy, Pandas, Polars, PyMC
- Infrastructure: AWS, Snowflake, Docker, GitHub
- Techniques & Tools:
+ Regression (with and without Bayesian priors)
+ Vector embeddings, similarity, clustering
+ Core statistics and distributions for EDA
+ Optimization methods (multi-armed bandit, mixed integer programming)
+ Causal inference and probabilistic modeling
What We’re Looking For
We’re seeking a technically curious engineer who thrives on turning theory into practice. The ideal candidate has:
- Strong experience implementing ML models in Python.
- Familiarity with regression, embeddings, causal inference, and optimization techniques.
- Experience applying statistical methods to exploratory data analysis.
- Comfort working with modern ML libraries and frameworks.
Bonus points if you have worked with:
- NLP tasks (LLMs, spaCy, neural networks).
- Recommender systems, latent factors, matrix factorization.
- Graph algorithms.
- Claude Code, Docker, and GitHub.ess computation engine.
Estimated Salary Range: $117,000-150,000Actual salary will be determined based on factors including, but not limited to, skill set and level of experience. This salary range is a good faith estimate of base pay. Strata also provides discretionary variable pay programs based on role. In addition, Strata provides a comprehensive benefits package including retirement benefits, health and welfare benefits, paid time off, parental leave, life and accident insurance, and other voluntary and well-being benefits.
Find out more about Strata benefits here.
How we work:The preferred location for this role is in Chicago, IL or St. Louis, MO. We value our people spending time together and have campuses hosting in-person events located in both cities. We are truly a hybrid environment with all team members experiencing the flexibility to work from home.
Thinking about applying?
Research shows that women and underrepresented groups tend to apply to jobs only when they check every box on a job posting. If you’re currently reading this and hesitating to click “Apply” for that reason, we encourage you to go for it! A true passion and excitement for making an impact is just as important as work experience.
Should you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please reach out to careers@stratadecision.com.
Here @ Strata…
Our culture is driven by our people solving problems together. We embrace learning, collaboration, and continuous career growth. Together, we lift our customers, our products, our company, and our community.
We believe that each of our team member’s unique perspectives and experiences is what drives innovation and positive change. Our individual differences are what make us a more forward-thinking organization. We foster a culture of inclusion, equity and belonging, regardless of race, religion, disability, sex, sexual orientation, gender identity or national origin.
Our Core Values:While we celebrate what makes each member of our team unique, our core values are what connect us. They set clear expectations for how we approach our work and how each of us can positively influence the experience of our team and our customers.
- We connect with positive intent.
- We are helpful.
- We own it.
- We get better every day.
- We are humble.
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- PyTorch
- NumPy
- Pandas
- Polars
- PyMC
- AWS
- Snowflake
- Docker
- GitHub
- Regression
- Causal Inference
- Optimization
- Vector Embeddings
- NLP
- LLM
- spaCy
- Neural Networks
- Recommender Systems
- Graph Algorithms
Возможные вопросы на собеседовании
Вакансия предполагает чтение и внедрение статей с arXiv. Важно понять, как кандидат подходит к этому процессу.
Расскажите о последней научной статье по ML, которую вы прочитали. Как бы вы подошли к реализации описанного в ней метода в нашей производственной среде?
В стеке упоминается причинно-следственный вывод, что редко встречается в стандартных ML-ролях.
В каких ситуациях вы бы предпочли использовать методы причинно-следственного вывода (causal inference) вместо стандартных моделей регрессии при анализе медицинских данных?
Компания работает с огромными объемами данных в здравоохранении.
Как вы обеспечиваете масштабируемость и производительность ML-моделей при работе с крупными наборами данных в Snowflake и AWS?
Упоминаются многорукие бандиты и смешанное целочисленное программирование.
Опишите ваш опыт работы с методами оптимизации. Можете ли вы привести пример задачи, где вы использовали многоруких бандитов?
Бонусные баллы даются за работу с LLM и NLP.
Как бы вы подошли к оценке качества (evaluation) ответов LLM-агента в контексте специфических медицинских или финансовых запросов?
Похожие вакансии
Data Scientist
Research Data Scientist
Research Data Scientist
Data Scientist - Commodities
Python Developer
Scientifique de données
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- США
- Зарплата
- 117 000 $ – 150 000 $