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Prepare coding + system design, plus applied AI: RAG/eval basics, latency/cost tradeoffs, failure modes, and how you’d instrument a model-backed feature end to end. Have 1–2 portfolio stories of production or prototype AI work.
Strong fit if you like owning AI features from idea to production in an on-site Austin role, and you can pair solid software craft with pragmatic model use—not only notebooks.
As an Applied AI Engineer at Quotewell, expect to ship models and tooling into real products: clarify business problems, prototype with LLMs/ML APIs, evaluate quality and cost, integrate with existing services, and partner with eng/product on production readiness and monitoring.
Build software + ML foundations with free paths:
The listing marks remote as no; expect work based in Austin, TX unless Quotewell states otherwise.
Usually production systems—APIs, evals, integration, and reliability—not pure research papers alone.
Use the free CERTS paths above for CS/software depth, then add hands-on LLM/ML projects you can demo.
Website: quotewell.com
Public cache only — not an employee review.
Quotewell is hiring an Applied AI Engineer for a full-time position based in Austin, TX. This role is ideal for professionals passionate about turning advanced machine learning concepts into practical, production-ready systems that deliver measurable value. The Opportunity As an Applied AI Engineer at Quotewell in Austin, TX, you will bridge research and real-world deployment by building intelligent systems that solve tangible business challenges. This full-time Applied AI Engineer opportunity invites you to shape how artificial intelligence is applied day in and day out within a collaborative local team setting focused on continuous improvement and technical excellence. Day-to-Day Responsibilities Design, prototype, and refine machine learning models tailored to specific use cases, iterating based on performance metrics and feedback. Integrate AI components into larger software architectures, ensuring reliability, scalability, and seamless user experiences. Process and analyze diverse datasets to train, evaluate, and fine-tune models using standard applied techniques. Collaborate with cross-functional colleagues to translate requirements into robust AI solutions and document technical approaches clearly. Monitor deployed systems, diagnose issues, optimize inference efficiency, and stay current with emerging methods in applied artificial intelligence. Experiment with established algorithms and frameworks to enhance model accuracy and efficiency for production environments. Requirements Proven experience building and shipping applied machine learning or AI systems in professional settings. Strong proficiency in Python and common libraries for data manipulation, model development, and evaluation. Solid understanding of core machine learning principles, including supervised learning, neural networks, and model deployment practices. Familiarity with frameworks such as PyTorch or TensorFlow and experience preparing data pipelines for training and inference. Ability to write clean, testable code and communicate technical findings effectively to both technical and non-technical audiences. Bachelor’s degree in computer science, engineering, mathematics, or a related field, or equivalent practical experience as an Applied AI Engineer. Why Join Quotewell Quotewell is hiring for this Applied AI Engineer role in Austin, TX and offers a supportive team environment that values technical growth and collaborative problem-solving. Applying for This Role To apply, complete your application directly on this page, or you'll be redirected to the employer's application platform to finish submitting there.
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