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職場(chǎng)數(shù)據(jù)點(diǎn)評(píng) 讓職場(chǎng)人少走彎路
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machine learning engineer

application engineer

Seeking talents passionate about ACGN culture.
Fully remote position open - Welcome to apply!

Responsibilities:
- Design, develop test ML models, covering Generative Model Language Model areas.
- Handle data processing work fML model training, including data cleaning, data preprocessing feature engineering.
- Manage the model training process: choose appropriate training methods, set parameters, continuously optimize models to achieve the best predictive performance.
- Work with MLOps engineers to realize the productization of ML models, continuously monitevaluate model performance.

Requirements:
- Have a full-time bachelor’s degree higher, in majors like Computer Science Communications; possess solid fundamental knowledge in computer science.
- Be proficient in PyTorch, TensorFlow other ML frameworks.
- Be proficient in Python programming.
- Be familiar with database management SQL; able to use data processing tools (such as Pandas) fdata cleaning preprocessing.
- Be familiar with key technologies processes flarge language models (LLMs) multimodal large models, such as model fine-tuning alignment.
- Be familiar with large model application development platforms tools like LangChain Dify.
- Have strong logical/probabilistic thinking skills; good at analyzing, summarizing, describing, communicating solving problems.
- Have a strong sense of responsibility team spirit; good at communication collaboration.
更新于 2026-03-24
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At ZF LIFETEC, we save lives through cutting-edge technology. With over 60 years of automotive safety innovation, we blend start-up agility with corporate stability to drive meaningful impact worldwide. Operating across 48 locations in 20 countries, our global presence amplifies our mission to make roads safer save lives.
Join us in a supportive dynamic environment committed to safety, innovation, reliability. As a part of our international team, your contributions spark innovations in automotive safety. Our inclusive diverse working environment promotes creativity, career growth, continuous development.

Your Tasks
Communication internally externally on technical information/issues.
Technical communication lead ftechnical issues
Lead/Support quality issue fplant during development post SoP (depends on the assignment)
Achieving of the internal technical release
Achieving of product release at the customer ? Support/Lead RFQ activities fthe assigned acquisition projects.
PPAC lead/support (depends on the assignment)

Your Profile
Well knowledge in development of SWS&DAB product
Well knowledge with PC application programs
Well communication skills active thinking
Well leadership skill ? Well program management skill
English knowledge, fluency in both written spoken, as interface are mostly external international

Why ZF LIFETEC?
Innovative Impact: Shape the future of safety with life-saving technology that truly matters.
Dynamic Workplace: Thrive in an agile, collaborative environment where every idea counts.
Culture of Excellence: Be part of a team with over 60 years of high standards groundbreaking achievements.
Growth & Empowerment: Advance your career with strong support fpersonal professional development.

Diversity & Inclusion
At ZF LIFETEC, we are committed to building a culture where inclusiveness thrives diversity is valued. We welcome unique perspectives actively work to remove barriers, empowering all employees to reach their full potential. Guided by this vision, we innovate life-saving technology that makes a real impact on automotive safety.
更新于 2026-01-30
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工資待遇區(qū)別

崗位名稱
平均工資
較上年
說明:machine learning engineer和application engineer哪個(gè)工資高?machine learning engineer高于application engineer。machine learning engineer平均工資¥27.9K/月,2026年工資¥K,application engineer平均工資¥21.4K/月,2026年工資¥K,統(tǒng)計(jì)依賴于各大平臺(tái)發(fā)布的公開數(shù)據(jù),系統(tǒng)穩(wěn)定性會(huì)影響客觀性,僅供參考。

就業(yè)前景區(qū)別(歷年招聘趨勢(shì))

崗位名稱
2025年職位量
較2024年
說明:machine learning engineer和application engineer哪個(gè)就業(yè)前景好?machine learning engineer2025年招聘職位量 13,與2024年持平。application engineer2025年招聘職位量 127,較2024年增長(zhǎng)了 2%。統(tǒng)計(jì)依賴于各大平臺(tái)發(fā)布的公開數(shù)據(jù),系統(tǒng)穩(wěn)定性會(huì)影響客觀性,僅供參考。

學(xué)歷要求區(qū)別

本科 65.4%
碩士 34.6%
本科 88.1%
碩士 6.8%
大專 3.4%
博士 1.7%
說明:machine learning engineer和application engineer的區(qū)別? machine learning engineer需要什么學(xué)歷?本科占65.4%,碩士占34.6%。 application engineer需要什么學(xué)歷?本科占88.1%,碩士占6.8%,大專占3.4%,博士占1.7%。

經(jīng)驗(yàn)要求區(qū)別

5-10年 34.6%
不限經(jīng)驗(yàn) 26.9%
3-5年 19.2%
應(yīng)屆畢業(yè)生 15.4%
1-3年 3.8%
5-10年 37.3%
3-5年 22.0%
1-3年 20.3%
不限經(jīng)驗(yàn) 20.3%
說明:machine learning engineer和application engineer的區(qū)別? machine learning engineer經(jīng)驗(yàn)要求哪個(gè)最多?5-10年占34.6%,不限經(jīng)驗(yàn)占26.9%,3-5年占19.2%,應(yīng)屆畢業(yè)生占15.4%,1-3年占3.8%。 application engineer經(jīng)驗(yàn)要求哪個(gè)最多?5-10年占37.3%,3-5年占22.0%,1-3年占20.3%,不限經(jīng)驗(yàn)占20.3%。

machine learning engineer與其他崗位進(jìn)行PK

application engineer與其他崗位進(jìn)行PK