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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** ALLOCATE LLC - **Location:** Palo Alto, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $165,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Cursor (Graphical User Interface Elements), Python (Programming Language), Machine Learning, Large Language Models, Git, Information Technology, Machine Learning Operations, Software Version Control - **Published:** July 11, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=84c53b5ddab5c2fc ## About the Role * 4+ years of applied ML / LLM engineering in production, with strong Python. * Experience taking models from prototype to reliable production systems. * Hands-on model fine-tuning and rigorous evaluation discipline. * Proficiency with Git and version control systems. * Hands-on experience with AI-assisted development tools such as Claude Code, OpenAI's Codex, or Cursor, and a demonstrated ability to incorporate new tools as they emerge. Nice to Haves * Applied NLP, computer vision, or multimodal models. * MLOps and model-monitoring tooling. * Background in fintech or financial data., * Bachelor's degree in Computer Science, a similar technical field, or equivalent practical experience. ## Description Allocate is looking to add an AI / Extraction Engineer to the team! There's a lot for us to build, and we need a strong engineer with a broad skillset who can jump right in to help us lay the technical foundation for the company's future., * Build, train, and improve machine-learning models for production use. * Develop evaluation and feedback loops that measurably improve model performance over time. * Stand up the tooling to measure, monitor, and track model quality. * Evaluate new models and techniques, and bring the best into production. * Collaborate cross-functionally to ship ML-powered capabilities., * Providing our clients with a world-class experience is our number one priority. We obsessively search for ways to improve the experience for our clients and partners-extraordinary response times, proactivity, and a top-tier experience in everything from product strategy to offline communications. * Challenge convention: Instead of detailing all the reasons an idea may not work, we question things to determine how a viable idea may be put into motion. * Commitment to continuous improvement: We find ways to personally scale each day by pushing ourselves up the learning curve. * Meritocracy, not politics: We place the utmost value on results and reward through merit, not political agendas. * Civil Discourse is embraced: Open, intellectually curious conversations are required to consistently arrive at the best decisions. Respect is paramount, but the mission is to get the right answer collectively, not to be right. * Embrace technological change: We adopt tools and techniques that make us faster, smarter, and better-especially around AI and automation-and drop outdated methods without hesitation. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Focoos AI: Building the Future of Computer Vision](https://www.wearedevelopers.com/videos/1659-focoos-ai-building-the-future-of-computer-vision) - [What non-automotive Machine Learning projects can learn from automotive Machine Learning projects](https://www.wearedevelopers.com/videos/397-what-non-automotive-machine-learning-projects-can-learn-from-automotive-machine-learning-projects) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction)