高级机器学习工程师
Senior Machine Learning Engineer
Clearview AI 是美国执法机构、州和联邦机构领先的面部识别技术提供商。我们的使命是通过负责任地使用我们的面部识别软件,帮助用户解决犯罪和预防金融欺诈。我们是一家充满激情、快速发展的初创公司,正在寻找热情且聪明的团队成员加入我们的团队。如需了解我们以及我们革命性的面部识别技术,请访问 。高级机器学习工程师
职位简介:我们正在招聘一位技术能力突出的个人贡献者,以推动我们在计算机视觉和机器学习方面的能力边界。这是一个高影响力、动手能力强的职位,适合希望构建和部署模型而非管理团队的研究型工程师。大部分工作涉及大规模视觉理解,从图像中提取结构化信号并推理照片背后的真实世界背景,但我们更看重深度学习/计算机视觉能力,而不是特定问题领域,欢迎优秀的通才。
职责:
- 构建、训练、评估和部署计算机视觉和多模态模型,将它们从早期原型推进到生产环境
- 设计系统,从图像中推断结构化属性和空间上下文,结合学习模型与几何和启发式推理
- 在大型、多样化的现实世界图像数据集上训练和微调模型,并构建可扩展的数据整理和标注流程
- 与视觉-语言模型(VLMs)合作,并构建严格的评估框架来衡量它们在我们任务中的准确性
- 开发并基准测试高性能图像检索能力,使用嵌入模型和向量索引策略
- 使用知识蒸馏、量化和 GPU 加速等技术优化模型的推理延迟和吞吐量
- 阅读最新研究,从学术文献中原型化新算法,并将有前景的想法转化为可靠的生产代码
- 实现高效、可扩展的数据流水线和推理基础设施
- 在机器学习和数据工程中开发高性能工具
- 根据主管或首席执行官的要求,完成其他合理的工作职责
要求和经验
要求:
- 具有在生产环境中构建、训练、评估和部署 ML 模型的经验
- 精通使用 PyTorch、JAX 或其他深度学习框架开发和优化模型
- 强大的软件工程能力
查看英文原文
Clearview AI is the leading provider of facial recognition technologies to US law enforcement, state, and federal agencies. Our mission is to help our users solve crimes and prevent financial fraud with the responsible use of our facial recognition software. Our company is a high-octane, fast growing startup looking to hire enthusiastic and intelligent team members to join our team. To learn more about us, and our revolutionary facial recognition technology, please visit .Senior Machine Learning Engineer
Position Summary: We are hiring a highly technical individual contributor to push the limits of our computer vision and machine learning capabilities. This is a high-impact, hands-on role for a research-minded engineer who wants to build and ship models, not manage a team. Much of the work involves large-scale visual understanding, extracting structured signals from imagery and reasoning about the real-world context behind a photograph, but we care more about deep ML/CV ability than any one problem area and welcome strong generalists.
Responsibilities:
- Build, train, evaluate, and deploy computer vision and multimodal models, taking them from early prototype through to production
- Design systems that infer structured attributes and spatial context from imagery, combining learned models with geometric and heuristic reasoning
- Train and fine-tune models on large, diverse real-world image datasets, and build the pipelines to curate and label that data at scale
- Work with vision-language models (VLMs) and build rigorous evaluation frameworks to measure their accuracy on our tasks
- Develop and benchmark high-performance image retrieval capabilities with embedding models and vector indexing strategies
- Optimize models for inference latency and throughput using techniques like distillation, quantization, and GPU acceleration
- Read current research, prototype novel algorithms from academic literature, and turn promising ideas into reliable production code
- Implement efficient, scalable data pipelines and inference infrastructure
- Develop high-performance tooling in ML and data engineering
- Additional duties and responsibilities as reasonably required by the employee’s supervisor or CEO
Requirements and Experience
Requirements:
- Experience building, training, evaluating, and deploying ML models in production
- Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models
- Strong software engineering ability to build and maintain complex systems and work with large-scale datasets
- Ability to solve open-ended problems and quickly learn new domains
- Comfort operating with significant ownership and autonomy, making pragmatic trade-offs between model sophistication, velocity, inference and business constraints
- BS, MS, or PhD in Computer Science or a related technical field, or equivalent practical experience
Nice to have:
- Experience inferring structured, real-world attributes from images
- Experience training models on large-scale, real-world image datasets
- Familiarity with vision-language models (VLMs)
- Ability to digest academic literature, prototype novel algorithms, and bridge the gap between research and production code
- Experience building LLM or VLM pipelines and the evaluation frameworks to measure their performance
- Experience in an ML role at a growth-stage startup
- Publications in major ML or computer vision conferences (e.g., CVPR, ICML, ICCV, WACV)
Benefits
- Medical, Dental, Vision, STD and LTD Plans
- FSA - Medical and Dependent Care
- EAP and wellness programs
- 13 Paid Holidays
- Unlimited PTO
- Flexible work environment - 100% remote
- 401(k) plan
Originally posted on Himalayas