Machine Learning Engineer
Role summary
This is a 24-month contract role for an onsite Machine Learning Engineer in Portland, OR. The position requires 5+ years of experience and a Bachelor's or Master's degree in a relevant field. The engineer will focus on machine learning, data science, and AI engineering, with strong programming skills in Python and its associated libraries. Key responsibilities include time-series data analysis, anomaly detection, causal inference, working with knowledge graphs, understanding explainable AI techniques, and deploying ML models into production. The role also involves problem-solving with complex datasets.
Job Description
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
Additional Information
All your information will be kept confidential according to EEO guidelines.
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