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Senior Applied Machine Learning Engineer, Asset Intelligence
Исключительно привлекательная вакансия в компании-единороге с оценкой $2.5 млрд. Предлагает работу над передовыми технологиями (LLM, IoT), высокую степень влияния на продукт и конкурентный компенсационный пакет с опционами.
Сложность вакансии
Высокая сложность обусловлена требованием более 7 лет опыта, наличием ученой степени (желательно) и необходимостью глубоких знаний как в классическом ML (временные ряды), так и в современных LLM-стеках. Роль подразумевает техническое лидерство и архитектурное проектирование сложных систем.
Анализ зарплаты
Указанная роль Senior ML Engineer в компании уровня Series D в Сан-Франциско обычно предполагает зарплату выше среднерыночной, дополненную значительным пакетом акций (equity). Наш прогноз базируется на данных для Tier-1 технологических компаний в США.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Applied Machine Learning Engineer position at MaintainX. With over 7 years of experience in developing and deploying production-grade ML systems, I am particularly drawn to your mission of transforming frontline operations through Asset Intelligence and LLM-powered workflows. My background in time-series modeling for anomaly detection and my proficiency with PyTorch and cloud ML stacks align perfectly with your goals for predictive maintenance.
In my previous roles, I have successfully led the architecture of end-to-end ML pipelines and mentored engineering teams to implement MLOps best practices. I am excited about the opportunity to leverage my expertise in LLM frameworks like LangChain and Hugging Face to build reasoning systems that empower the global workforce. I am confident that my technical leadership and passion for industrial IoT will contribute significantly to MaintainX's next phase of growth following your impressive Series D funding.
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Откликнитесь в maintainx уже сейчас
Присоединяйтесь к лидеру индустрии Industrial AI и создавайте будущее предиктивного обслуживания вместе с MaintainX!
Описание вакансии
MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.
We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.
Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.
As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.
The Role
We are seeking a highly skilled and motivated Senior Applied Machine Learning Engineer to guide the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives.
You’ll combine deep ML expertise with strong software engineering and leadership skills—mentoring engineers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites.
This role sits at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX’s predictive and generative AI strategy.
What you’ll do:
- Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products.
- Architect end-to-end ML systems—from data ingestion and feature engineering to model training, deployment, and monitoring.
- Mentor a growing team of ML and data engineers, instilling best practices for experimentation, evaluation, and model lifecycle management.
- Partner with product and engineering leaders to align AI roadmap with customer needs and business goals.
- Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining.
- Drive performance optimization through techniques like quantization, distillation, and scalable inference serving.
- Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence.
- Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security.
About you:
- 7+ years of experience in Machine Learning, Data Science, or Applied AI.
- Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar).
- Proven experience deploying production ML systems—not just prototypes—at scale.
- Strong background in LLMs, time-series modeling, and anomaly detection for real-world data.
- Demonstrated ability to lead architectural decisions, mentor engineers, and collaborate across product, data, and platform teams.
- Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
- Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.
Bonus skills:
- Experience with OCR for extracting structured data from documents.
- Background in time-series modeling for predictive maintenance and anomaly detection.
- Familiarity with Industrial IoT systems (sensors, telemetry, edge computing).
- Experience applying reinforcement learning or agentic architectures for decision-making and control systems.
- Contributions to open-source ML frameworks or research in reliability, explainability, or digital twins.
What’s in it for you:
- Competitive salary and meaningful equity opportunities.
- Healthcare, dental, and vision coverage.
- 401(k) / RRSP enrollment program.
- Take what you need PTO.
- A high impact Culture:
- You’ll work with Smart, Humble Optimists across the globe.
- Meritocratic environment where ideas and outcomes are publicly celebrated.
About us:
We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.
MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
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Навыки
- Python
- PyTorch
- TensorFlow
- AWS
- Databricks
- LLM
- LangChain
- LlamaIndex
- Hugging Face
- Docker
- Kubernetes
- MLflow
- SageMaker
- Weights & Biases
- Time Series Analysis
- Anomaly Detection
- IoT
- OCR
- Reinforcement Learning
Возможные вопросы на собеседовании
Проверка опыта работы с основным доменом компании — предиктивным обслуживанием.
Расскажите о вашем опыте работы с временными рядами для обнаружения аномалий: какие алгоритмы вы использовали и как решали проблему ложноположительных срабатываний?
Оценка навыков проектирования масштабируемых систем.
Как бы вы спроектировали архитектуру для обработки телеметрии с тысяч IoT-датчиков в реальном времени для последующей подачи в ML-модель?
Проверка актуальных знаний в области генеративного ИИ.
Каким образом вы планируете интегрировать LLM и агентные архитектуры (например, LangChain) в продукт для управления активами?
Оценка опыта в MLOps и вывода моделей в продакшн.
Опишите ваш подход к мониторингу качества моделей после деплоя и процесс автоматизированного переобучения (feedback loops).
Проверка лидерских качеств и навыков менторства.
Как вы подходите к код-ревью и установлению стандартов разработки в ML-команде?
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