Machine Learning Engineer

Cynet Systems • San Jose, CA

1d

About The Position

We are seeking a skilled Machine Learning Engineer with a strong background in building and deploying machine learning models, particularly in the realm of Generative AI. The role involves designing, developing, and fine-tuning AI solutions using models like Google's Gemini for various tasks including information extraction, document summarization, and report generation. You will architect and implement advanced Retrieval-Augmented Generation (RAG) systems, research and apply emerging GenAI techniques, and deploy a wide range of ML models on Google Cloud Platform. This position requires building and maintaining robust MLOps pipelines, conducting deep data analysis, and collaborating closely with cross-functional teams to deliver integrated AI/ML solutions. A key aspect of this role is championing best practices in software engineering and MLOps to ensure the quality and scalability of our machine learning systems, while staying current with the latest advancements in the ML and GenAI landscape.

Requirements

• 3+ years of professional experience building and deploying machine learning models in a production environment.
• Advanced proficiency in Python and its core data science/ML libraries (e.g., PyTorch, scikit-learn, Pandas).
• Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
• Demonstrable, hands-on experience in prompt engineering and/or fine-tuning Large Language Models (e.g., Gemini).
• Hands-on experience with a major cloud provider, with a strong preference for Google Cloud Platform (GCP).
• Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD).
• Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.

Nice To Haves

• Master's or PhD in a relevant field.
• Specific experience with GCP services like Vertex AI, BigQuery, Google Cloud Storage, and GKE.
• Experience building RAG systems from the ground up.
• Proven ability to lead technical projects and mentor other engineers.

Responsibilities

• Design, develop, and fine-tune Generative AI solutions using models like Google's Gemini for tasks such as information extraction, document summarization, and report generation.
• Architect and implement advanced Retrieval-Augmented Generation (RAG) systems to enhance model accuracy and provide verifiable, context-aware responses.
• Research and apply emerging GenAI techniques, such as agentic frameworks, to build more autonomous and capable systems.
• Design and deploy a wide range of ML models (classification, regression, forecasting, etc.) on Google Cloud Platform.
• Build and maintain robust, automated MLOps pipelines for data preprocessing, feature engineering, model training, validation, and deployment using tools like Vertex AI and BigQuery.
• Conduct deep data analysis to uncover insights, validate hypotheses, and guide feature engineering for improved model performance.
• Partner closely with data scientists, software engineers, and other business stakeholders to frame problem statements, define technical requirements and deliver integrated AI/ML solutions.
• Champion best practices in software engineering and MLOps to ensure the quality, maintainability, and scalability of machine learning systems.
• Continuously evaluate and stay current with the latest advancements in the ML and GenAI landscape.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level