Senior AI/ML Engineer

Overview

On Site
Depends on Experience
Contract - W2

Skills

Generative Artificial Intelligence (AI)
Artificial Intelligence
Machine Learning (ML)
Large Language Models (LLMs)
TensorFlow
Regression Analysis
Prompt Engineering
scikit-learn
PyTorch
Deep Learning
Clustering
Machine Learning Operations (ML Ops)

Job Details

Title: Senior AI/ML Engineer

Location: Novato, CA

About the Role:

We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), Deep Learning, and Classic Machine Learning, with secondary exposure to Computer Vision, Agentic AI systems, and MLOps. You will work closely with cross-functional teams to build intelligent, scalable, and production-ready AI systems.

Key Responsibilities

  • Develop and fine-tune Generative AI models (LLMs, RAG, Prompt Engineering, Agentic AI systems) for enterprise-grade use cases.
  • Design, implement, and evaluate machine learning models (regression, classification, clustering).
  • Build and optimize deep learning architectures (CNNs, RNNs, Transformers, Neural Networks).
  • Apply computer vision techniques such as image classification, object detection, segmentation, and OCR.
  • Perform data preprocessing, feature engineering, and model evaluation to ensure high performance and reliability.
  • Implement model training, hyperparameter tuning, and optimization workflows.
  • Leverage frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face to build scalable ML pipelines.
  • Integrate AI solutions with AI APIs and tools (LangChain, OpenAI APIs, Vector Databases like Pinecone/FAISS).
  • Collaborate with engineering teams to apply MLOps practices (model deployment, monitoring, CI/CD).
  • Utilize cloud platforms (AWS, Google Cloud Platform, Azure) and containerization technologies (Docker, Kubernetes) for scalable deployment.
  • Apply strong mathematical/statistical foundations to solve optimization and probability-based problems.

Required Skills (Must Have)

  • Generative AI: LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), Agentic AI
  • Classic Machine Learning: Regression, Classification, Clustering
  • Deep Learning: CNN, RNN, Transformers, Neural Networks
  • Frameworks: TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face
  • Programming: Python, SQL

Secondary / Good-to-Have Skills

  • Computer Vision: OpenCV, YOLO, Detectron2
  • Agentic AI systems & autonomous workflows
  • AI APIs & Tools: LangChain, OpenAI APIs, Vector Databases (Pinecone, FAISS)
  • MLOps (Model Deployment, Monitoring, CI/CD)
  • Cloud Platforms: AWS, Google Cloud Platform, Azure
  • Containerization & Orchestration: Docker, Kubernetes

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.