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Robert Bosch Venture Capital

Venture capital funding deep tech startups

AI Expert

Computer Vision +1Confirmed live in the last 24 hours
Full-timeWuxi, Jiangsu, ChinaNo salary listedIn-person

About the Job

Requirements

  • A Master's degree or above in Computer Science, Computer Vision, AI/ML, Electrical Engineering, or a closely related field is required.
  • At least 3 years of hands-on experience in real AI/ML projects is required, including at least 1 year in Agentic AI, LLM application development, or equivalent.
  • A proven track record of delivering AI solutions from prototype to production in an industrial or manufacturing environment is required.
  • Experience with Coding Agents such as Claude Code, OpenAI Codex or Codex CLI, GitHub Copilot Workspace, or Cursor is required.
  • Experience building and running multi-agent systems with LangGraph, AutoGen, CrewAI, or similar agentic orchestration frameworks is required.
  • Proficiency in LLM API integration, including OpenAI, Anthropic Claude, Azure OpenAI, or open-source LLMs through Ollama or vLLM, is required.
  • Skill in Retrieval-Augmented Generation (RAG), including vector databases such as Chroma, Weaviate, Qdrant, or pgvector; embedding pipelines; and context management, is required.
  • Familiarity with prompt engineering patterns, including chain-of-thought, few-shot, tool-calling, structured output, and self-reflection loops, is required.
  • Understanding of agent safety, including output guardrails, hallucination detection, human-in-the-loop design, and audit trails, is required.
  • Familiarity with MCP (Model Context Protocol) or comparable agent-tool integration standards is required.
  • Expertise in Python and proficiency in PyTorch and/or TensorFlow/Keras are required.
  • Strength in classical image processing using OpenCV, including filtering, edge detection, feature extraction, and camera calibration, is required.
  • A deep understanding of CNN architectures, including AlexNet, VGG, ResNet, DenseNet, MobileNet, and EfficientNet, is required.
  • Proficiency in object detection methods (YOLO, Faster-RCNN, SSD, DETR) and segmentation methods (Mask-RCNN, SAM) is required.
  • Experience with Vision Transformers (ViT, Swin) and multimodal models (CLIP, LLaVA, GPT-4V) is required.
  • Familiarity with data labelling toolchains (Label Studio, CVAT) and data versioning (DVC, MLflow) is required.
  • Knowledge of model optimisation for edge deployment, including quantisation, pruning, ONNX, and TensorRT, is required.
  • Proficiency in Git and CI/CD pipelines for ML/AI systems is required.
  • Experience with containerisation using Docker and Kubernetes for agent and model serving is required.
  • Familiarity with cloud/on-prem ML platforms such as Azure ML, AWS SageMaker, or equivalent is required.
  • Experience with experiment tracking using MLflow or W&B and model registry practices is required.
  • Ability to translate ambiguous manufacturing or business problems into well-scoped AI solutions is required.
  • Mandarin working proficiency and English professional proficiency are required.
  • The candidate must have a proactive, self-driven learning mindset and a customer-oriented, Continuous Improvement attitude.
  • The candidate must have strong analytical and structured problem-solving skills.
  • The candidate must be able to present complex AI topics to non-technical stakeholders.
  • Intercultural collaboration experience and comfort working in cross-functional, international teams are required.

Responsibilities

  • Identify agentic opportunities across RBCD manufacturing operations and translate business cases into technical agent architectures and implementation roadmaps.
  • Design, develop, and deploy AI agents using modern agentic frameworks such as LangGraph, AutoGen, and CrewAI, integrated into the M.AI.Co platform.
  • Use coding agents such as Claude Code, OpenAI Codex, and GitHub Copilot Workspace to accelerate agent and tool development, applying prompt engineering, tool-use, and multi-agent orchestration patterns.
  • Architect multi-agent pipelines combining LLMs, vision models, retrieval-augmented generation, and structured data to deliver end-to-end automated workflows.
  • Build and maintain safety guardrails for production agent deployments, including human-in-the-loop checkpoints, output validation, audit logging, and risk control frameworks.
  • Manage agent data assets by defining retrieval strategy, knowledge-base architecture, and context window optimisation to ensure agents have accurate, up-to-date information.
  • Lead end-to-end development of computer vision and deep learning algorithms for AOI (Automatic Optical Inspection) and manufacturing quality processes, from proof of concept to serial implementation.
  • Design and implement model architectures, including CNN, Transformer-based ViT, and multimodal models, 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.
  • Lead or accompany cross-functional project teams, taking full responsibility for costs, quality, and on-time delivery.
  • Coordinate AI work packages within RBCD manufacturing and cooperate with PS central departments to deploy and share standard solutions across plants.
  • Coach and mentor data enthusiasts and team members, and drive AI competency development, including Agentic AI literacy across the organisation.
  • Monitor the latest AI developments, including foundation models, agentic frameworks, and coding agents, and evaluate their applicability to RBCD use cases.
  • Lead or develop analysis models and algorithms for improvement projects, with full responsibility for costs, quality, and on-time delivery.
  • Cooperate with PS central departments to deploy and share standard solutions.
  • Coach and guide data enthusiasts and team members, supporting their competency development.

About the Company

Robert Bosch Venture Capital

Venture capital funding deep tech startups

RBVC (Robert Bosch Venture Capital) is a global venture capital firm that backs early-stage deep tech startups in areas like energy efficiency, medical devices, and virtual/augmented reality. It supports companies with funding and access to Bosch’s network and resources to help them scale and bring innovations to market. Unlike traditional VCs, RBVC may purchase solutions for a proof-of-concept while allowing startups to keep their intellectual property, which speeds up development and lowers upfront costs. The firm earns money through equity investments and the eventual success of its portfolio. RBVC’s goal is to accelerate technological advances across multiple industries by connecting startups with Bosch’s ecosystem, customers (from medical centers to data centers), and global reach.

Company size
201-500
Company stage
Not listed
Total funding
$3.8B
Headquarters
Frankfurt, Germany
Founded
2007

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