AI/ML Engineer

Title: AI/ML Engineer (Contract - Hybrid, Bay Area)
Location: Bay Area (Hybrid)
Duration: Contract

Overview:
We are seeking an experienced AI/ML Engineer for a contract position in the Bay Area. The ideal candidate will have a strong background in machine learning model deployment, Retrieval-Augmented Generation (RAG) architecture, and optimizing models for precision and recall. This role requires a hands-on engineer who can design, develop, and deploy AI/ML solutions while ensuring high-performance outcomes.

Responsibilities:

• Design, develop, and deploy machine learning models into production environments.
• Implement and optimize Retrieval-Augmented Generation (RAG) architectures to improve AI-driven applications.
• Evaluate and fine-tune models to maximize precision and recall based on business needs.
• Develop and maintain scalable ML pipelines for model training, testing, and deployment.
• Collaborate with cross-functional teams including data engineers, software developers, and product managers to integrate AI solutions.
• Monitor model performance, troubleshoot issues, and implement improvements.
• Ensure compliance with best practices for data privacy, security, and ethical AI use.

Required Qualifications:

• 5+ years of experience in AI/ML engineering with a focus on model deployment.
• Hands-on experience with Retrieval-Augmented Generation (RAG) architectures.
• Strong understanding of precision, recall, and other model evaluation metrics.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
• Experience with cloud platforms (AWS, GCP, or Azure) for deploying ML models.
• Familiarity with MLOps practices, CI/CD for machine learning, and containerization (Docker, Kubernetes).
• Experience working with vector databases and retrieval-based AI systems.
• Strong problem-solving skills and ability to work in a hybrid, fast-paced environment.

Preferred Qualifications:

• Experience with LLM fine-tuning and optimization.
• Knowledge of knowledge graphs, embeddings, and search optimization techniques.
• Background in NLP and generative AI applications.

If you are passionate about AI/ML and want to contribute to cutting-edge projects, we encourage you to apply!

the software development lifecycle - must have participated on many projects through their complete lifecycles (requirements, design, development, launch).