Machine Learning Engineer

Lowongan diperbarui 2 bulan yang lalu

Deskripsi Pekerjaan

The ideal candidate will have industry experience working on a range of recommendation, classification, and optimization problems. 

You will bring the ability to own the whole ML life cycle, define projects and drive excellence across teams. 

You will work alongside the world’s leading engineers and researchers to solve some of the most exciting and massive social data and prediction problems that exist on the web.

Persyaratan

  • 5+ years of experience in these areas machine learning, recommendation systems, pattern recognition or data mining
  • Proven experience to translate insights into business recommendations
  • Experience with Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable
  • Knowledge developing and debugging in C/C++ and Java
  • Suggest, collect and synthesize requirements and create effective feature roadmaps
  • Solid background of ML domains (NLP, computer vision, recommendation, anomaly detection, graph learning), algorithms (deep learning, gradient boosted trees, optimization), and best practices, (e.g. skew minimization, A/B testing, feature engineering, model selection)
  • Familiar with PyTorch, TensorFlow, Spark, Airflow and other LLMs.
1
Diperlukan pengalaman selama 5 tahun
250 ~ 500 TWD / tahun
100% Kerja Remote
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Tentang Kami

Morgan Philips is a global talent solutions provider with over 600 consultants in 22 countries. Founded in 2013 in Paris, we've grown rapidly through the opening of new offices in key locations. In Asia, we have close to 150 employees across 8 offices and provide top-quality services across 15 industries to over 1000 clients. We leverage our powerful global database, Club5000 network, and research centers staffed by talent mapping experts to provide unparalleled access to top-tier talent for our clients.

Asia Offices:

Singapore, Hong Kong, Taiwan, Shanghai, Beijing, Guangzhou, Shenzhen, and Zhuhai.

Our Brand in Taiwan:

Morgan Philips Executive Search, Fyte


Tim

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Pekerjaan

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1
1 jt ~ 2 jt TWD / bulan
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Full-time
Level Pemula
1
70 rb ~ 110 rb TWD / bulan
Simpan

Full-time
Level Menengah-Senior
1
120 ~ 160 TWD / tahun
Simpan