机器学习工程师 – 生成式AI与大语言模型
ML Engineer – Generative AI & LLMs
机器学习工程师，对使用大语言模型和真实数据构建前沿系统充满热情。在此职位中，你将与客户和团队成员紧密合作，设计、原型设计并实现可扩展的机器学习解决方案。
你将加入一个协作性强、表现优异的团队，重视清晰的思考、务实的执行和持续学习。如果你在快节奏环境中表现出色，喜欢解决开放性问题，并且非常重视工作的质量和影响力，我们期待与你联系。
- 必备条件：精通大语言模型工程，熟悉主流大语言模型供应商及其最佳实践。有构建或使用代理系统（例如工具使用、记忆、规划、多代理协作）的经验是加分项。请展示你的大语言模型项目，并详细说明你的职责和贡献。
- 具备快速原型设计前沿工具和研究想法的能力，有将原型转化为生产就绪服务的记录。
- 有统计学和机器学习的实际经验。熟练使用 Python 机器学习栈：Pandas、Numpy、scikit-learn、XGBoost、PyTorch 等。熟悉开发工具如 Git、Docker、SQL、Bash 和 FastAPI。
- 具备强大的分析思维和商业意识；能够批判性地思考数据及其对产品或业务结果的影响。
- 计算机科学或相关工程领域（涉及编程）的学士学位或更高学历（例如硕士或博士）。
- 加分项：熟悉 AWS 或 Azure、GitHub Actions、Spark、Neo4j Cypher 和图数据库。
我们提供具有竞争力的薪酬。
我们相信责任担当，而非微观管理。
你将加入由来自 Facebook、Uber、Amazon 和 Google 的世界级工程师和数据科学家组成的团队。我们是一家位于多伦多的快速发展的咨询公司，客户涵盖从构建有影响力的科技初创企业到希望扩大工程和数据能力的财富 500 强公司。
最初发布于喜马拉雅山
查看英文原文
We’re looking for Machine Learning Engineers who are passionate about building cutting-edge systems with LLMs and real-world data. In this role, you’ll work closely with clients and teammates to design, prototype, and productize scalable machine learning solutions.
You’ll be part of a collaborative, high-performing team that values clear thinking, pragmatic execution, and continuous learning. If you thrive in fast-paced environments, enjoy tackling open-ended problems, and care deeply about the quality and impact of your work, we’d love to connect.
- Must have: Expertise in LLM engineering, including familiarity with popular LLM providers and their best practices. Experience building or working with agentic systems (e.g. tool use, memory, planning, multi-agent coordination) is a strong plus. Show us your LLM projects and detail your ownership and contributions.
- Strong ability to rapidly prototype cutting-edge tools and research ideas, with a track record of turning prototypes into production-ready services.
- Hands-on experience with statistics and machine learning. Comfortable working with the Python ML stack: Pandas, Numpy, scikit-learn, XGBoost, PyTorch, etc. Proficient with development tools such as Git, Docker, SQL, Bash, and FastAPI.
- Strong analytical mindset and business acumen; able to think critically about data and its impact on product or business outcomes.
- Bachelor's degree or higher (e.g., MS or PhD) in Computer Science or a related engineering field involving coding.
- Bonus: Familiarity with AWS or Azure, GitHub Actions, Spark, Neo4j Cypher, and graph databases.
We have competitive compensation.
We believe in accountability and NOT micro-management.
You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities.
Originally posted on Himalayas