AI/ML Engineer - Telecom Background

AI/ML Engineer

Location: Bellevue, WA (Onsite)

Type: Contract - C2C/W2/1099

Locals preferred.

Experience

• At least 10+ years of total IT Experience as a developer.
• At least 2+ years working with latest AI/ML toolsets

Role Overview

We are seeking an AI/ML Engineer with strong experience in the telecom domain to design, develop, and deploy machine learning solutions that enhance network performance, customer experience, and operational efficiency. The ideal candidate combines solid ML engineering skills with domain knowledge in telecom systems such as OSS/BSS, network optimization, and subscriber analytics.

Key Responsibilities

• Design, build, and deploy scalable machine learning models for telecom use cases (e.g., churn prediction, network fault detection, traffic forecasting, anomaly detection).
• Work with large-scale structured and unstructured telecom data (CDRs, network logs, KPI metrics).
• Collaborate with network engineers, data engineers, and product teams to translate business problems into ML solutions.
• Develop data pipelines and feature engineering workflows for real-time and batch processing.
• Optimize and monitor model performance in production environments.
• Apply deep learning, statistical modeling, and time-series forecasting techniques where appropriate.
• Ensure model interpretability, reliability, and compliance with data governance standards.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or related field.
• 3+ years of experience in AI/ML engineering with production deployments.
• Strong expertise in deep learning frameworks (PyTorch, TensorFlow) and ML libraries (Scikit-learn, XGBoost).
• Hands-on experience with LLMs, transformers, and generative AI frameworks (e.g., Hugging Face, LangChain, vector databases like FAISS, Pinecone).
• Proficiency in Python and experience with API development (FastAPI/Flask).
• Experience with data engineering and big data ecosystems (Spark, Kafka, Hadoop).
• Strong knowledge of MLOps tools (MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Solid understanding of telecom data structures (CDRs, OSS/BSS, network KPIs).

Preferred Qualifications

• Prior experience in telecom operators or telecom analytics projects.
• Knowledge of 4G/5G networks, RF optimization, or network planning.
• Experience with real-time streaming platforms (Kafka, Flink).
• Familiarity with cloud platforms (AWS, Azure, GCP).
• Exposure to MLOps practices and CI/CD pipelines for ML.

Key Competencies

• Strong analytical and problem-solving skills.
• Ability to work with cross-functional teams in a fast-paced environment.
• Effective communication of technical concepts to non-technical stakeholders.