| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
Binance | Taipei, Taiwan |
| |||
Zscaler | Remote | $119k - $170k | |||
Zscaler | Remote | $92k - $120k | |||
Zinnia | Remote | $122k - $123k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Kraken | London, United Kingdom | $77k - $101k | |||
Kraken | London, United Kingdom | $80k - $117k | |||
Bloxstaking | Remote | $82k - $112k | |||
Bitmex | Remote | $117k - $130k | |||
Coins.ph | Manila, Philippines | $96k - $150k | |||
Bcbgroup | Remote | $122k - $141k | |||
Bcbgroup | Remote | $59k - $80k | |||
Zscaler | Remote | $119k - $170k | |||
Jumpcrypto | Remote | $150k - $200k | |||
Kraken | London, United Kingdom | $90k - $100k | |||
Falconx | Remote | $106k - $109k |
Binance Accelerator Program - AI Engineering
Responsibilities
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Participate in the design, development, and maintenance of AI-related components, including model serving, inference modules, and associated toolchain development.
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Participate in LLM evaluation work, including effectiveness assessment, benchmark construction, and experimental analysis, as well as assist in model performance optimization.
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Contribute to system performance, stability, and reliability improvements, driving engineering optimizations such as inference efficiency and resource utilization.
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Participate in the design and implementation of AI solutions for business scenarios, including but not limited to Agent, RAG, and AIGC applications.
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Collaborate with product, algorithm, and engineering teams to drive the adoption and iteration of AI capabilities in real-world business contexts.
Requirements
1. Basic Requirements
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Currently pursuing a Bachelor's degree or above in Computer Science, Artificial Intelligence, Software Engineering, or a related field.
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Available to intern at least 3 days per week; internship duration of 6 months or more is preferred.
2. Technical Skills (Core Requirements)
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Solid programming fundamentals with proficiency in Python (required) and good coding practices.
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Basic understanding of backend development (API design, service development, etc.).
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Familiarity with at least one deep learning framework (PyTorch / TensorFlow).
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Basic understanding of large language models (LLMs), such as Transformer architecture, fine-tuning, and inference pipelines.
3. Bonus Skills (Strongly Preferred)
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Experience or knowledge in Prompt Engineering / RAG / Agent.
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Experience with model evaluation (benchmarks, automated assessment).
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Familiarity with frameworks such as LangChain / LlamaIndex / Dify / Coze is a plus.
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Prior project experience in AIGC, dialogue systems, or intelligent agents is a plus.
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Familiarity with Linux environments and basic debugging skills.
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Knowledge of Docker / Kubernetes / distributed systems is a plus.
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Some understanding of system performance optimization (latency, throughput, resource utilization).
Is Kubernetes high demand?
Yes, Kubernetes is currently in high demand in the technology industry
Kubernetes is an open-source container orchestration platform that is widely used for deploying, scaling, and managing containerized applications
It provides a standardized way to manage and automate the deployment of containerized applications across multiple hosts and provides benefits such as reliability, scalability, and flexibility
As more and more organizations move towards containerized architectures, Kubernetes has become a critical component of their infrastructure
Kubernetes is used by companies of all sizes, from startups to large enterprises, and across various industries, including finance, healthcare, and e-commerce
According to various job market and salary surveys, Kubernetes-related skills are in high demand, and job positions related to Kubernetes are growing at a rapid pace
In fact, Kubernetes is often listed as one of the top skills that are in high demand by technology companies
Overall, Kubernetes is a highly sought-after skill in the technology industry, and it's likely to remain in high demand in the foreseeable future as more and more organizations adopt containerization and cloud-native architectures.