位于北京市, c22的 6 个优质deep learning engineer职位（正在招聘！）

Forward Deployed AI Manager
Accenture —北京市
- 全职
7天
Senior Product Designer
Duolingo —北京市
Generative AI Engineer, Image/Video Restoration
Apple —北京市
AI Software and GPU Kernel Development Eng.
Advanced Micro Devices, Inc —北京市
10天
DWS Enterprise AI Product Manager
Lenovo —北京市
14天
Senior Staff/Staff Machine Learning Engineer
Coupang —北京市
快速申请

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Research Scientist - Reinforcement Learning (北京)_CR
Bosch Group —北京市
Conduct reserach in reinforcement learning （RL）, deep learning, and optimization. Strong programming skills, proficiency in mainstream deep learning frameworks,…
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Account Manager, MICE - Shanghai & Beijing
Kuoni Tumlare —北京市
This role requires a deep understanding of the event management industry and a strong ability to translate client requirements into exceptional event solutions.
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Forward Deployed AI Manager

Accenture -
北京市

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职位详情

全职
7 天前

完整职位描述

Role Description

This is not a consulting role. It is not a project delivery role. It is not a research position. A Forward Deployed AI Engineer is a production engineer who works embedded inside a client's enterprise, shoulder to shoulder with their teams, to make complex AI platforms work in real, messy organizational environments. You own outcomes: time-to-value, adoption, reliability, and scalability. Not delivery milestones. Outcomes.

The market is beginning to understand what leading technology companies have demonstrated: AI products fail not because the models are weak but because deployment is broken. The gap between a successful AI pilot and an AI capability that scales is bridged by engineers who can translate platform capability into measurable business value inside a real enterprise environment. That is this role.

Forward Deployed AI Engineers form the execution spine of our Reinvention Deployment Engineering pods. We are building the largest FDE capability in the services industry. The engineers who join at this stage will define what the role looks like at scale and will have access to the hardest enterprise AI problems in the market across every industry.

Key Responsibilities

Lead enterprise AI platform deployments across complex multi-stakeholder client environments — Anthropic, OpenAI, Microsoft, Google, Salesforce, SAP, or Palantir — owning the full programmed from architecture through adoption
Own programmed-level delivery outcomes: time-to-value, reliability, adoption velocity, and scalability across multiple concurrent workstreams, with commercial metrics attached
Lead rapid experimentation at pace: drive ambiguous business problems to working production systems in days or weeks across complex enterprise environments
Architect and govern enterprise AI solutions across the full technology stack: identity, data, security, governance, platform layer, and multi-system workflow integration at programmed scale
Shape AI reinvention strategy for client CTO, CFO, and CISO: build value architecture, ROI backlogs, use case prioritization frameworks, and multi-year AI adoption roadmaps
Define and publish reusable reinvention blueprints, patterns, and accelerators that scale across multiple client engagements and grow the FDE practice
Lead architecture design sessions, executive workshops, and code-with sessions with client engineering and C-suite leadership teams
Codify delivery learnings, failure patterns, and engineering standards that shape the FDE practice and enable the next generation of forward deployed engineers

Basic Qualifications

8-10 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
Minimum of 1 years of deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
Minimum of 7 years of experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
8-10 years of experience leading software engineering teams: overseeing delivery, allocating resources across workstreams, and owning the professional development of direct reports"
Demonstrated end-to-end delivery ownership in a client-embedded environment, internal projects, vendor labs, or team-only deployments do not qualify
Proven ability to articulate business value: can quantify the impact of deployments in terms a CFO would recognize and act on
Experience presenting to and building trust with senior client stakeholders, CTO, CFO, or CISO level
Non-linear profiles are expected and welcomed, assessment is based on demonstrated deployment experience and outcome ownership, not CV pattern matching
People lead responsibilities: experience managing, developing, and performance-managing a team of engineers; setting individual development plans and conducting career conversations

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在北京市, c22的deep learning engineer个职位

Forward Deployed AI Manager

Senior Product Designer

Generative AI Engineer, Image/Video Restoration

AI Software and GPU Kernel Development Eng.

DWS Enterprise AI Product Manager

Senior Staff/Staff Machine Learning Engineer

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在北京市, c22的deep learning engineer个职位

Senior Product Designer

Generative AI Engineer, Image/Video Restoration

AI Software and GPU Kernel Development Eng.

DWS Enterprise AI Product Manager

Senior Staff/Staff Machine Learning Engineer

Other jobs to consider

我想收到关于 北京市, c22 的 deep learning engineer 的最新职位提醒

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