Machine Learning Engineer

TLDR

Develop machine learning models using various techniques and tools to solve complex problems across different domains, maintaining production systems and exploring innovative solutions.

Job Title: Machine Learning Engineer
Location: Portland, OR - Onsite (Local only / F2F interview)
Duration: 24 Months Contract

Experience Level: 5+ years of experience

Required Qualifications
•    Bachelor’s or master’s degree in computer science, Machine Learning, Electrical Engineering, or related field 
•    5+ years of experience in machine learning, data science, or AI engineering 
•    Strong programming skills in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) 
•    Experience with time-series data analysis and anomaly detection 
•    Hands-on experience with causal inference methods (e.g., Bayesian networks, structural causal models) 
•    Experience building or working with knowledge graphs (Neo4j, RDF, graph databases) 
•    Understanding of explainable AI techniques (SHAP, LIME, counterfactual analysis) 
•    Experience deploying ML models in production systems 
•    Strong problem-solving skills and ability to work with complex, real-world datasets

Preferred Qualifications
•    Experience with fault tree analysis (FTA), reliability engineering, or failure analysis 
•    Background in industrial systems, semiconductors, manufacturing, or IoT environments 
•    Experience with graph-based ML / Graph Neural Networks (GNNs) 
•    Familiarity with RCA methodologies (FMEA, 5 Whys, fishbone diagrams) 
•    Experience with vector databases, RAG systems, or LLM-based reasoning 
•    Knowledge of MLOps practices (CI/CD, monitoring, model governance) 
•    Experience working in air-gapped or high-security environments 
 

All your information will be kept confidential according to EEO guidelines.

Chabez Tech builds scalable, cloud-native data engineering and AI products that empower organizations to transform their data ecosystems. We work with enterprises across various industries to create robust data platforms and enhance operational efficiency, making data-driven excellence achievable.

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