Design, build, and productionize advanced ML and LLM-based systems for intelligent document understanding and compliance automation. Focus on architecture, optimization, and real-world deployment. Develop robust CI/CD pipelines for continuous training and monitoring of ML models.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
TalentDome Staffing is helping recruit for an AI startup in Florida that is building a neutral compliance layer for large, document-heavy workflows in financial services. The platform uses AI to classify, validate, and extract data from complex files at scale, transforming manual review into a faster, more accurate, and auditable process.
About the Role
As a Machine Learning Engineer, you will design, build, and productionize advanced ML and LLM-based systems that power intelligent document understanding and compliance automation. This is a hands-on engineering role focused on architecture, optimization, and real-world deployment.
What You’ll Do
- Design, prototype, and deploy machine learning and LLM-based systems (Python, LangChain, LLaMA / LLaMA 3, small language models).
- Build agentic AI workflows that classify, split, and extract data from complex document sets, ensuring accuracy and auditability.
- Develop RAG (Retrieval-Augmented Generation) pipelines for structured, semi-structured, and unstructured data—including large PDFs and data feeds.
- Lead document AI tasks such as classification, entity extraction, table parsing, signature/notary detection, and document type labeling.
- Optimize models for efficiency using LoRA/QLoRA, retrieval tuning, evaluation, and latency/cost reduction.
- Implement robust CI/CD pipelines for continuous training, retraining, and monitoring of ML models.
What You’ll Bring
- 7+ years professional experience in software development with strong AI/ML background
- Hands-on experience as ML Engineer in your current and/or last role and Python expertise;
- Deep understanding of LLMs (Large Language Models) and SLMs (Small Language Models), including architecture and deployment Experience with small OR large language models (SML/LLM), including open source SMLs, trained using LoRA and LoRAX.
- Proven experience deploying LLMs/SLMs in private or secure cloud environments (not public APIs)
- Background in model quantization (reducing model size and optimizing performance for deployment)
- Knowledge of continuous training / retraining pipelines and how to maintain updated models efficiently Experience with LangChain, LLama, and agentic AI workflows
- Ability to design and build AI systems that process multi-architecture, multi-structured, and document-based data
- Proven track record shipping to production (end-to-end: prototyping → deployment → monitoring)
- Startup mindset: hands-on, execution-driven, and ownership-oriented.
Why Join
- Salary up to $180K + equity
- Fully remote within the U.S.
- Opportunity to work on cutting-edge AI infrastructure solving complex real-world problems
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