15 个优质control algorithm职位（正在招聘！）

AI Expert_PS
Bosch Group —无锡市
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Trexquant Investment —北京市
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Renesas Electronics —上海市
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Western Digital —深圳市
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Bosch Group —无锡市
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Lifebyte Systems —深圳市
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Johnson Electric International Limited —江门市
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Bosch Group —上海市
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Bosch Group —无锡市
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AI Expert_PS

Bosch Group -
无锡市

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职位详情

完整职位描述

Company Description

Bosch Powertrain Systems Co., Ltd. (RBCD), the joint venture of Robert Bosch GmbH and Weifu High Technology Group Co., Ltd., is a high tech enterprise specializing in the development, production and sales of common rail systems, exhaust gas after treatment systems, fuel cell stacks and key components. The company, based on its local R&D and project management competence, with innovative technologies, can support customers to continuously improve internal combustion engines efficiency, to reduce emission, and to accelerate the market launch of new energy products. The garget of the company is to provide the Chinese market and customers with diversified advanced powertrain products.

Job Description

Job Summary

As an AI Expert in RBCD/TEF4, you will be a core builder of Bosch's AI-Native Operations in BBM-CN. You will design and develop Agentic AI systems – autonomous AI agents that work side-by-side with our operations teams to continuously improve manufacturing and business processes through the M.AI.Co (Mobility AI Copilot) platform. Beyond classical computer vision and deep learning, you will own the full agentic development cycle: from opportunity identification and agent architecture, to data governance, safety guardrails, and production-grade deployment.

Roles and Responsibilities
- Agentic AI Development

Identify agentic opportunities across RBCD manufacturing operations; translate business cases into technical agent architectures and implementation roadmaps.
Design, develop, and deploy AI agents using modern agentic frameworks (LangGraph, AutoGen, CrewAI, or equivalent) integrated into the M.AI.Co platform.
Leverage Coding Agents (Claude Code, OpenAI Codex, GitHub Copilot Workspace) to accelerate agent and tool development; apply prompt engineering, tool-use, and multi-agent orchestration patterns.
Architect multi-agent pipelines that combine LLMs, vision models, retrieval-augmented generation (RAG), and structured data to deliver end-to-end automated workflows.
Build and maintain safety guardrails: human-in-the-loop checkpoints, output validation, audit logging, and risk control frameworks for production agent deployments.
Manage agent data assets — define retrieval strategy, knowledge-base architecture, and context window optimization to ensure agents have accurate, up-to-date information.

- Computer Vision & Classical AI

Lead end-to-end development of computer vision and deep learning algorithms for AOI (Automatic Optical Inspection) and manufacturing quality processes — from PoC to serial implementation.
Design and implement model architectures (CNN, Transformer-based ViT, multimodal) for classification, detection, segmentation, and anomaly detection tasks.
Establish data collection, labelling, and data management strategies to enable fast model iteration and continuous performance improvement.
Collaborate with IT, machine, and product technical experts to define data pipelines, storage concepts, and MLOps practices.

- Leadership & Knowledge Sharing

Lead or accompany cross-functional project teams, taking full responsibility for costs, quality, and on-time delivery.
Coordinate AI work packages within RBCD manufacturing; cooperate with PS central departments to deploy and share standard solutions across plants.
Coach and mentor data enthusiasts and team members; drive AI competency build-up including Agentic AI literacy across the organisation.
Proactively monitor the latest AI developments (foundation models, agentic frameworks, coding agents) and evaluate their applicability to RBCD use cases. Authority ( mandatory for Grade 7 and above, optional for others )
Lead or develop analysis model, algorithms for improvement projects with full responsibility for costs, quality, and on-time delivery.
Cooperate with PS central department to deploy / sharing the standard solutions.
Coaching and guiding data enthusiasm and team members supporting them competency build up

Qualifications

Master's degree (or above) in Computer Science, Computer Vision, AI/ML, Electrical Engineering, or a closely related field.
3+ years of hands-on experience in real AI/ML projects, with at least 1 year in Agentic AI, LLM application development, or equivalent.
Proven track record of delivering AI solutions from prototype to production in an industrial or manufacturing environment.
Strong proactive, self-driven learning mindset with a customer-oriented and CIP (Continuous Improvement) attitude. Job Relevant Knowledge and Experience
Agentic AI & LLM Engineering
Hands-on experience with Coding Agents: Claude Code (Anthropic), OpenAI Codex / Codex CLI, GitHub Copilot Workspace, or Cursor.
Experience building and running multi-agent systems with LangGraph, AutoGen, CrewAI, or similar agentic orchestration frameworks.
Proficient in LLM API integration (OpenAI, Anthropic Claude, Azure OpenAI, open-source LLMs via Ollama / vLLM).
Skilled in Retrieval-Augmented Generation (RAG): vector databases (Chroma, Weaviate, Qdrant, pgvector), embedding pipelines, context management.
Familiar with prompt engineering patterns: chain-of-thought, few-shot, tool-calling, structured output, and self-reflection loops.
Understanding of agent safety: output guardrails, hallucination detection, human-in-the-loop design, audit trails.
Familiar with MCP (Model Context Protocol) or comparable agent-tool integration standards.

Computer Vision & Deep Learning
Expert in Python; proficient in PyTorch and/or TensorFlow/Keras.
Strong in classical image processing (OpenCV): filtering, edge detection, feature extraction, camera calibration.
Deep understanding of CNN architectures: AlexNet, VGG, ResNet, DenseNet, MobileNet, EfficientNet.
Proficient in object detection (YOLO, Faster-RCNN, SSD, DETR) and segmentation (Mask-RCNN, SAM).
Experience with Vision Transformers (ViT, Swin) and multimodal models (CLIP, LLaVA, GPT-4V).
Familiar with data labelling toolchains (Label Studio, CVAT) and data versioning (DVC, MLflow).
Knowledge of model optimisation for edge deployment: quantisation, pruning, ONNX, TensorRT.

MLOps & Engineering Practices
Proficient in Git and CI/CD pipelines for ML/AI systems.
Experience with containerisation (Docker, Kubernetes) for agent and model serving.
Familiar with cloud/on-prem ML platforms (Azure ML, AWS SageMaker, or equivalent).
Experience with experiment tracking (MLflow, W&B) and model registry practices.

Domain & Soft Skills
Ability to translate ambiguous manufacturing/business problems into well-scoped AI solutions.
Strong analytical and structured problem-solving skills.
Excellent communication skills — able to present complex AI topics to non-technical stakeholders.
Intercultural collaboration experience; comfortable working in cross-functional, international teams.
Mandarin (working proficiency) and English (professional proficiency) required.

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control algorithm 个职位

AI Expert_PS

Electrical Engineer

Co-Head of Quantitative Research (CHINA)

Sr. Manager/Director of Robotics Architect team

Technologist, firmware engineering

Advanced Electrical Engineer

Lead Product Manager, Ad Serving & Ranking, Demand and Ads Team

JMP_ Vehicle Simulation Expert – Truck Systems Modeling

Senior C++ Engineer

功能安全经理(底盘领域)_ITK

Principal Engineer, Intelligent Manufacturing

电机系统设计专家_EM

Security Software Engineer_XC

资深电机控制软件开发工程师_BCSC

Data Artist

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