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LLM Engineer United States Jobs (Hybrid work)

4 Job Offers

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ML Engineer, LLM's
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Join Knowtex as an ML Engineer/Researcher focused on LLMs, building voice AI for clinical documentation. Requires 4+ years ML experience, PyTorch skills, and LLM fine-tuning expertise. Hybrid role in San Francisco with equity and unlimited PTO.
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Knowtex
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Until further notice
Machine Learning Engineer, Inference & Serving (Speech LLM) - San Francisco
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195000.00 - 365000.00 USD / Year
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Plaud
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Until further notice
Machine Learning Engineer, Speech LLM Training - San Francisco
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Plaud
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Ai / Llm Systems Engineer
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We are seeking a Junior to Mid-Level AI/LLM Systems Engineer to build foundational AI systems in Culver City, CA. You will develop reusable LLM-based architectures, training workflows, and agent frameworks using Python. This role offers high technical ownership, work/life balance, and benefits in...
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110000.00 - 150000.00 USD / Year
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Snail Games
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Until further notice

About the LLM Engineer role

Explore the cutting-edge field of LLM Engineer jobs, a pivotal role at the intersection of artificial intelligence and software engineering. LLM Engineers are specialized professionals responsible for building, integrating, and maintaining applications powered by Large Language Models. They transform groundbreaking AI research into reliable, scalable, and valuable products that solve real-world problems across industries like healthcare, finance, customer service, and more. This profession is central to the AI revolution, focusing on making advanced language models practical, efficient, and safe for end-users.

In their day-to-day work, LLM Engineers tackle a diverse set of responsibilities. A core duty involves designing and deploying robust LLM services and APIs for text-based applications, which includes everything from chatbots and content generation systems to complex analytical tools. They architect and implement Retrieval-Augmented Generation (RAG) systems to enhance model accuracy with external knowledge sources, leveraging vector databases and semantic search. Engineers in this field are also deeply involved in prompt engineering, developing strategies to reliably steer model outputs and creating frameworks for managing prompts at scale. Furthermore, they collaborate closely with machine learning scientists, data engineers, and product teams to align technical development with business objectives, ensuring LLM initiatives deliver tangible value.

The role demands a strong technical skill set. Proficiency in Python is fundamental, along with hands-on experience with LLM frameworks and tools such as LangChain and LlamaIndex. A solid understanding of transformer architectures and embedding techniques is crucial. LLM Engineers must be adept at the full lifecycle of AI deployment—from prototyping and systematic evaluation using custom metrics for accuracy and bias, to production-grade integration and ongoing optimization for performance and cost. They also engage with modern MLOps and LLMOps practices to establish scalable, maintainable workflows. Beyond technical prowess, successful professionals possess a problem-solving mindset, adaptability in fast-paced environments, and the ability to communicate complex concepts to cross-functional stakeholders. For those passionate about shaping the future of AI, LLM Engineer jobs offer a dynamic and impactful career path building the intelligent systems of tomorrow.