Cardinal Integrated Technologies Inc · 2 months ago
ML Engineer with LLM + Agentic AI
United States
Full-time
Remote
Mid Level
3+ years expCardinal Integrated Technologies Inc is seeking a skilled and forward-looking Machine Learning Engineer with expertise in Large Language Models (LLMs), Generative AI, and Agentic Architectures to join their growing R&D and Applied AI team. This role is pivotal in helping the company deliver the next generation of agentic AI systems for enterprise spend management and risk controls, collaborating closely with AI/ML researchers and product teams to design and optimize intelligent systems.
BankingInformation TechnologyInsurancePharmaceuticalWeb Development
Responsibilities
Design, train, fine-tune, and deploy ML/LLM models for production
Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases
Prototype and optimize multi-agent workflows using LangChain, LangGraph, and MCP
Develop prompt engineering, optimization, and safety techniques for agentic LLM interactions
Integrate memory, evidence packs, and explainability modules into agentic pipelines
Work with multiple LLM ecosystems, including:
OpenAI GPT (GPT-4, GPT-4o, fine-tuned GPTs)
Anthropic Claude (Claude 2/3 for reasoning and safety-aligned workflows)
Google Gemini (multimodal reasoning, advanced RAG integration)
Meta LLaMA (fine-tuned/custom models for domain-specific tasks)
Collaborate with Data Engineering to build and maintain real-time and batch data pipelines supporting ML/LLM workloads
Conduct feature engineering, preprocessing, and embedding generation for structured and unstructured data
Implement model monitoring, drift detection, and retraining pipelines
Utilize cloud ML platforms such as AWS SageMaker and Databricks ML for experimentation and scaling
Explore and evaluate emerging LLM/SLM architectures and agent orchestration patterns
Experiment with generative AI and multimodal models (text, images, structured financial data)
Collaborate with R&D to prototype autonomous resolution agents, anomaly detection models, and reasoning engines
Translate research prototypes into production-ready components
Work cross-functionally with R&D, Data Science, Product, and Engineering teams to deliver AI-driven business features
Participate in architecture discussions, design reviews, and model evaluations
Document experiments, processes, and results for effective knowledge sharing
Mentor junior engineers and contribute to best practices in ML engineering
Qualification
Required
Experience designing, training, fine-tuning, and deploying LLM/ML models for production
Hands-on experience with RAG (Retrieval-Augmented Generation) pipelines using vector databases
Proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, Scikit-learn, and Hugging Face Transformers
Experience with multi-agent frameworks such as LangChain, LangGraph, or MCP
Experience working with LLM ecosystems (OpenAI GPT, Anthropic Claude, Google Gemini, Meta LLaMA)
Strong understanding of the ML lifecycle including data preparation, training, evaluation, deployment, and monitoring
Experience building and maintaining real-time/batch data pipelines and ML infrastructure (AWS SageMaker, Databricks ML)
Experience implementing AI safety, explainability, and guardrail mechanisms for responsible AI development
Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field
3+ years of experience building and deploying ML systems
Strong programming skills in Python, with experience in PyTorch, TensorFlow, Scikit-learn, and Hugging Face Transformers
Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference optimization)
Demonstrated expertise in at least two of the following: OpenAI GPT (chat, assistants, fine-tuning), Anthropic Claude (safety-first reasoning, summarization), Google Gemini (multimodal reasoning, enterprise APIs), Meta LLaMA (open-source fine-tuned models)
Familiarity with vector databases, embeddings, and RAG pipelines
Proficiency in handling structured and unstructured data at scale
Working knowledge of SQL and distributed frameworks such as Spark or Ray
Strong understanding of the ML lifecycle — from data prep and training to deployment and monitoring
Preferred
Experience in enterprise spend management, risk controls, or financial data analytics
Relevant AI/ML or Cloud certifications (AWS Certified Machine Learning Specialty, TensorFlow Developer, or equivalent)
Experience with agentic frameworks such as LangChain, LangGraph, MCP, or AutoGen
Knowledge of AI safety, guardrails, and explainability
Hands-on experience deploying ML/LLM solutions in AWS, GCP, or Azure
Experience with MLOps practices — CI/CD, monitoring, and observability
Background in anomaly detection, fraud/risk modeling, or behavioral analytics
Contributions to open-source AI/ML projects or applied research publications
Company
Cardinal Integrated Technologies Inc
We are a company of IT professionals who passionately believe that good quality products & services are delivered by great resources.
201-500 employees
H1B Sponsorship
Cardinal Integrated Technologies Inc 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
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Distribution of Different Job Fields Receiving Sponsorship
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Trends of Total Sponsorships
2025 (5)
2024 (1)
2023 (3)
2022 (5)
2021 (4)
2020 (4)
Funding
Current Stage
Growth StageCompany data provided by crunchbase