发现心仪岗位

Role Overview

We operate a large-scale CI/CD infrastructure built on GitLab Docker Runners. We are looking for an extremely meticulous engineer with a "perfectionist" mindset to drive the standardization and automation of our infrastructure — elevating it to a professional, scalable, and fully traceable environment. You will architect and own the Ansible framework that governs our entire node fleet, while leveraging AI tools to push the boundaries of operational efficiency.

Key Responsibilities

1. Infrastructure Automation: Maintain, integrate, and build a comprehensive Ansible framework. Consolidate fragmented configurations into a unified Infrastructure as Code (IaC) system with full version control and auditability.

2. Physical Excellence (The "OCD" Task): Full ownership of rack cabling, labeling, and hardware health audits. We demand a professional, traceable, and perfectly organized hardware environment.

3. AI-Driven Efficiency:

- Proactively use AI to accelerate Ansible development, log analysis, and rapid debugging.

- The Human Guardrail: Provide the critical judgment that AI lacks—auditing AI-generated code for security and physical-world logic.

4. Debug & Optimization: Assist in troubleshooting Runner failures, conduct comparative (A/B) testing between nodes, and optimize Runner tagging/performance.

5. Access Control: Manage IP bindings, routing tables, and SSH public key distribution.

Requirements

1. Methodical Perfectionist: Zero tolerance for messy cabling, unorganized documentation, or inconsistent configurations.

2. Ansible & Linux Expert: Proven experience in consolidating fragmented systems into automated workflows (Debian/Raspbian).

3. AI-Savvy: Demonstrated ability to use AI tools (Copilot, Claude, Cursor, etc.) to solve technical problems faster than traditional methods.

4. Analytical Mindset: Patient and logical in debugging; Able to trace root causes across large distributed fleets without losing rigor or precision.

岗位职责

1、牵头搭建并优化公司全面预算管理体系，跟踪预算执行、做差异分析并输出报告，推动预算动态落地优化；

2、定期出具月/季/年度经营分析报告，拆解核心经营指标与各业务板块盈利能力，为产品定价、客户结构及资源分配提供数据支撑，同时针对业务关键场景输出专项财务分析，助力业务决策、防控经营风险；

3、搭建适配行业模式的财务模型，开展收入、成本、现金流及盈利预测，结合行业动态迭代模型；

4、联动业务部门提供专业财务支持，优化 FP&A 工作流程，推动业财数据打通，并配合内外部审计，保障财务工作合规规范；

5、对标行业标杆完善财务规划分析体系，提升专业能力；

6、完成上级交办的其他相关工作。

任职要求

1、要求本科及以上财务、经济类相关专业，持有 CPA、ACCA、AAIA 等证书优先；

2、3 年以上 FP&A 相关经验，熟悉半导体行业流程者优先考虑；

3、熟练运用 Excel 及财务建模，可独立搭建各类财务模型，熟悉主流财务系统及 BI 工具者优先；

4、具备优秀跨部门沟通协作能力，工作严谨负责、抗压能力强；

5、有良好英文读写水平和出色的报告撰写能力；

6、拥有业务洞察力和战略思维，能为企业经营决策提供专业财务支持。

岗位职责

1、负责 EHS 体系搭建、制度落地及合规管控，对标国家及地方法规标准，规避企业 EHS 合规风险；

2、环境管理：统筹环境评估、污染防治、危废合规处置及节能减排工作，保障企业环保合规运营；

3、职业健康管理：建立员工健康管理制度，监测职场健康状况，落实防护举措，预防职业病及职场意外伤害；

4、安全管理：开展安全风险评估与隐患排查，落实安全制度与全员培训，防范安全事故，高效处置突发险情；

5、事故应急：建立事故预防机制，负责各类事故、未遂事件的调查溯源、整改闭环及上报工作，杜绝同类问题复发；

6、合规管控：实时跟进 EHS 最新法规政策，动态优化管理制度，确保企业各项 EHS 工作合规达标；

7、数据汇报：汇总分析 EHS 相关数据，梳理风险与管理问题，输出工作报告，为管理层决策提供依据；

8、外联协同：对接政府相关部门，统筹内外部沟通协调，保障企业顺利通过各类 EHS核查审核；

9、培训文化：组织 EHS、安全、消防专项培训及主题活动，提升全员安全合规意识，营造安全生产氛围；

10、完成上级交办的其他工作及各类综合行政辅助事务。

任职要求

1、本科及以上学历，环保、安全、质量、品控等相关专业优先；

2、持有注册安全工程师或安全生产管理人员证书；具备 3 年及以上 EHS 管理经验，具备成功通过 ISO14001/ISO45001 体系认证相关工作经验；

3、熟悉 ISO14001、ISO45001 体系条文，持有体系内审员证书，精通国内及上海地区废水、废气、固废等环保法规；

4、具备扎实的 EHS 专业及法规知识，对接处理政府、客户及内部各类 EHS 检查；

5、工作严谨负责、具备主人翁意识，优秀的沟通协调、组织推动及问题解决能力；擅长应急处置、方案规划、文案汇报，主动学习行业新规，严格把控工作质量。

岗位职责

1、主导现金流预测，统筹集团资金池管理，优化头寸与使用效率，编制相关报告；

2、负责境内外资金业务（账户管理、跨境登记）及合规操作；

3、管理操作风险、利率风险、市场风险等，确保资金安全和收益；

4、维护账户信息体系，配合内外部审计；

5、推动资金管理系统与流程优化，参与数字化建设；

6、支持业务板块资金需求，提供投融资、跨境资金解决方案；

7、维护银行及金融机构合作关系；

8、完成上级交办的其他任务。

任职要求

1、财会、金融、经济等相关专业本科及以上学历；有集团或金融机构资金管理经验者优先；

2、熟悉资金管理、结算、外汇、理财等业务，了解金融市场及风险管理工具；

3、掌握财税法规及跨境资金管理制度，有集团或金融机构资金管理经验者优先；

4、具备现金流预测、资金统筹优化意识及风险评估能力，并能制定闲置资金运作方案；

5、沟通协调能力强，能高效对接内外部机构；

6、具备数据分析与报告撰写能力；

7、工作细致，执行力强。

Role Overview

Design compiler technologies that translate AI models into optimized code for the RISC-V AI SoC. You will focus on IR design, code generation, autotuning, and ensuring clean integration with upstream toolchains (LLVM, MLIR, TVM).

Key Responsibilities

1. Extend MLIR/LLVM to support vector and matrix instruction sets.

2. Implement optimization and lowering passes for AI operators.

3. Build compiler interfaces compatible with ecosystem conventions.

4. Integrate autotuning and performance modeling.

5. Collaborate with runtime and kernel teams to align code generation strategies.

Qualifications

1. 4+ years in compiler backend or performance optimization.

2. Strong C++/Python proficiency.

3. Familiarity with MLIR, LLVM, TVM, or XLA.

Preferred Attributes

1. Experience integrating custom instructions or intrinsics 

2. Knowledge of AI model graph-to-code lowering workflows.

3. Familiarity with autotuning systems like AutoTVM or MLIR-based tuners.

4. Understanding of mixed-precision compute and performance trade-offs.

Impact: You enable portable, high-performance compilation pipelines that power ecosystem integration.

Role Overview

You will develop, optimize, and demonstrate end-to-end AI applications and reference designs on the proprietary RISC-V AI SoC and SDK. This includes benchmarking, demos, and workload enablement to showcase platform capabilities and provide ready-to-use examples for developers and customers.

Key Responsibilities

1. Develop and port AI workloads (CNN, Transformer, multimodal) using PyTorch, TensorFlow, and ONNX on the SDK. 

2. Create reference designs combining compiler, runtime, and kernel components. 

3. Develop SDK demos, tutorials, and reproducible benchmarking pipelines. 

4. Optimize models for performance, accuracy, and power efficiency. 

5. Collaborate with compiler, runtime, and framework teams to debug and tune workloads. 

6. Deliver performance analysis reports and reference application repositories. 

7. Collect usability feedback from internal and external developers. 

Qualifications

1. 3–7 years of experience in AI model development, optimization, or deployment. 

2. Strong hands-on with PyTorch, TensorFlow, or ONNX Runtime. 

3. Experience running AI workloads on GPU, NPU, or heterogeneous compute systems. 

4. Strong Python skills; C++ proficiency preferred. 

Preferred Attributes

1. Familiarity with quantization, mixed precision, and compiler-based model optimization. 

2. Experience creating AI SDK demos, sample apps, or developer documentation. 

3. Understanding of CNN, transformer, and attention-based models.