Juno · 3 days ago
Mid–Senior Level LLMOps Engineer
United States
Full-time
Remote
Mid, Senior Level
$150K/yr - $200K/yr
5+ years expJuno is a fast-growing AI company focused on solving real problems for tax accounting firms. They are seeking a mid-senior level LLMOps Engineer to build scalable applications and manage LLM fine-tuning and ML Ops processes.
Computer Software
Responsibilities
Fine-tune and adapt large language models and vision-language models for data extraction from unstructured and semi-structured sources
Orchestrate fine-tuning workflows using tools such as Google Vertex AI, OpenAI fine-tuning APIs, and Hugging Face
Automate model lifecycle management including training triggers, artifact versioning, promotion between environments, and rollback strategies
Implement CI/CD pipelines for LLMs, including automated testing, evaluation gates, and safe production releases
Work closely with AI Engineers to take their prompting strategies and fine-tuning approaches and turn them into repeatable, scalable production workflows
Partner on prompt and model versioning strategies to ensure reproducibility and auditability
Translate experimental wins into robust, production-ready systems
Design and implement evaluation frameworks to measure model performance, reliability, and downstream impact
Build regression testing pipelines to detect accuracy drops as data or models change
Create and maintain live dashboards tracking model accuracy, drift, latency, and cost
Establish alerting and quality thresholds to proactively catch performance degradation
Map extracted entities and relationships into graph-based knowledge representations
Collaborate on schema design and entity resolution strategies to support scalable knowledge bases
Build and maintain ML Ops pipelines, including model deployment, monitoring, versioning, and retraining
Maintain full lineage across datasets, prompts, model versions, and deployments
Support auditability and reproducibility requirements critical to financial workflows
Work closely with product managers, researchers, and engineers to translate business and domain requirements into effective AI solutions
Contribute to architectural discussions and technical decision-making
Qualification
Required
5–8+ years of experience in ML Ops, platform engineering, or applied machine learning roles
Prior hands-on experience in MLOps is required, including deploying, monitoring, and maintaining ML models in production
Prior experience working with LLMs via APIs (e.g., OpenAI, Hugging Face, or similar)
Strong proficiency in Python and modern LLM frameworks (e.g., Langgraph, PydanticAI, OpenAI API, Vertex AI)
Hands-on experience fine-tuning LLMs and/or vision models in production settings
Practical experience with ML Ops, including deployment and monitoring of models
Solid understanding of model evaluation, data quality, and performance trade-offs
Experience working with knowledge graphs, graph databases, or entity resolution systems
Familiarity with multimodal models, document processing, or OCR pipelines
Prior experience in AI research, applied research, or high-growth startups
Preferred
Experience with structured output validation and extraction-style LLM tasks
Familiarity with RAG systems, prompt versioning, or adapter-based fine-tuning (LoRA)
Experience operating ML systems in regulated or high-accuracy domains (finance, legal, healthcare)
Company
Juno
We’re modernizing tax work by equipping tax pros with the tools they've always wanted.
11-50 employees
H1B Sponsorship
Juno has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
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Trends of Total Sponsorships
2024 (1)
2022 (1)
2021 (1)
Funding
Current Stage
Early StageCompany data provided by crunchbase