> Markdown version of [/jobs/ext/1009476-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/1009476-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** Ai In Bumble Inc. - **Location:** Austin, TX, United States - **Experience:** Expert - **Salary:** $220,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Airflow, Data Analysis, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Software Deployment, Feature Engineering, Pytorch, Large Language Models, Apache Spark, Model Validation, Build Management, Machine Learning Operations, Data Pipelines - **Published:** June 9, 2026 - **Apply:** https://www.dice.com/job-detail/d89b09b1-f49d-462d-9809-e641169e2edf ## About the Role * Typically requires 5-8 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.> * Strong experience building and deploying machine learning models in production environments> * Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow)> * Experience working with data pipelines and distributed systems (e.g. Spark, Airflow) to support ML workflows> * Familiarity with experimentation methodologies such as A/B testing and model evaluation techniques> * Ability to collaborate effectively across functions, demonstrating strong ownership and a collaborative mindset> * Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes> * Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsibly>, Will be determined based on factors such as the selected candidate's qualifications, relevant experience, skill set, and other job-related considerations. ## Description As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data exploration through to production deployment, while collaborating closely with Product, Engineering, and Data partners. You'll bring curiosity into how we experiment, iterate, and improve, and you'll role model our values of Curiosity and Excellence by continuously raising the bar in how we build and apply AI. AI is deeply embedded in how we evolve at Bumble. In this role, you'll independently apply modern machine learning and emerging AI techniques, contributing to scalable systems while ensuring thoughtful, responsible use of AI in everything we ship. What you'll do * Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement> * Own problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment> * Develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery> * Apply modern ML frameworks (e.g. PyTorch or TensorFlow) to design, train, and optimise models in production environments> * Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset> * Collaborate cross-functionally with Product and Engineering, working with purpose to translate product questions into ML solutions> * Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor> * Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment> ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)