Algorithm/ Machine Learning Engineer (Abnormal Detection)
atBinance
Feb 13
Founded by Changpeng Zhao (CZ) in 2017, Binance is currently the largest cryptocurrency exchange in terms of daily volume. Binance is the core global exchange. However, Binance operates separate exchanges in some countries such as the US, UK, Singapore, and Turkey due to regulatory reasons.
Since Binance has global operations, the exchange does a lot of hiring on a regular basis. Being a market leader, Binance Jobs also come with significant perks. Most of the jobs are remote, with flexible working hours. Binance also offers health insurance, the option to be paid in crypto, and programs to develop your skills.
If you're looking for Binance US Jobs, a wide range of them are also available most of the time. On average, the Binance Interview process lasts 2-4 weeks with 4 steps: Application Review, Interview, Offer, and finally Onboarding.
Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 250 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.
Responsibilities:
- Responsible for the development and algorithm optimization of abnormal detection, root cause analysis and other functions of monitoring products
- Focus on cutting-edge technologies and trends in AiOps field to drive algorithm and product optimization
Requirements:
- More than 5 years working experience
- Good foundation of program development, familiar with Python, Java, Spark, Flink and other distributed computing platforms.
- Familiar with machine learning and deep learning algorithms, such as logistic regression, tree model, ensemble learning, temporal data correlation algorithms ARIMA, LSTM, CNN, etc.
- Familiar with machine learning related development frameworks, such as Numpy, Sklearn, Tensorflow, PyTorch, etc., experience in practical application and optimization of algorithm projects.
- Experience in anomaly detection or root cause analysis related to monitoring products is preferred.
- AiOps related experience is preferred.
- LLM related experience is preferred.
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