AI/ML Engineer

Cloud Blue Technology looking for a versatile and experienced Machine Learning Engineer (Contractor) to support our data engineering and analytics initiatives on Google Cloud Platform (Google Cloud Platform). The ideal candidate will bring expertise in unsupervised machine learning, experimentation, generative AI, and data visualization, and will help build scalable solutions that uncover insights and drive business decisions.

While experience with unsupervised learning (e.g., clustering, anomaly detection, dimensionality reduction) is highly preferred, we welcome candidates with a broader ML background who are passionate about solving complex data problems and visualizing results effectively.

Key Responsibilities:

Design and implement unsupervised ML models to extract insights from structured and unstructured data
Develop generative AI solutions for data augmentation, summarization, and visual storytelling
Create interactive and compelling visualizations using traditional and GenAI tools
Collaborate with full-stack development and platform engineering teams to integrate ML models into production systems
Build scalable ML pipelines using Google Cloud Platform-native services such as BigQuery, Vertex AI, Dataflow, and Cloud Functions
Ensure model performance, reliability, and maintainability through iterative experimentation and optimization
Document methodologies and present findings to both technical and non-technical stakeholders
Required Qualifications:

Strong experience with unsupervised machine learning techniques and algorithms
Hands-on experience with Google Cloud Platform services including BigQuery, Vertex AI, Cloud Storage, and Dataflow
Experience collaborating with full-stack teams to integrate ML solutions via APIs or microservices
Proficiency in Python (including libraries like scikit-learn, TensorFlow, PyTorch) and SQL
Experience with data visualization tools (e.g., Looker Studio, Plotly, Tableau) and GenAI platforms
Solid understanding of statistics, feature engineering, and data preprocessing
Ability to communicate complex findings through visual storytelling and presentations
Familiarity with MLOps practices and model deployment in cloud environments
Preferred Qualifications:

Knowledge of self-supervised learning or graph-based ML approaches
Experience using GenAI frameworks and platforms such as:
Vertex AI GenAI Studio for prompt engineering and model tuning
OpenAI API for text generation, summarization, and embeddings
Hugging Face Transformers for custom model deployment and fine-tuning
LangChain, LlamaIndex, or similar frameworks for GenAI-powered applications
RunwayML, Stability AI, or DALL E for generative visualizations
Prior experience in a consulting or contractor role
Google Cloud Platform certification (e.g., Professional Machine Learning Engineer or Data Engineer)