AI engineer

Job#: 3030923

Job Description: AI Engineer

Location: REMOTE

Employment Type: Contract to Perm

This is a hands‑on engineering role where you will own individual use cases end‑to‑end, from data exploration and feature engineering through model development and production deployment. You will work alongside a Senior ML/AI Engineer and report to the Director, ACE. You will operate within the architecture and MLOps standards set by the team while having the autonomy to drive your own projects to completion.

• Develop, train, evaluate, and deploy ML/AI models across a range of use cases including classification, regression, anomaly detection, NLP, and generative AI.
• Build and maintain data pipelines and feature engineering workflows that feed production models.
• Write clean, tested, production‑quality code and participate in peer code reviews.
• Monitor model performance in production and implement retraining workflows when drift or degradation is detected.
• Work with network telemetry and time‑series data to build anomaly detection and predictive maintenance models.
• Develop NLP and speech models for call summarization, sentiment analysis, and agent assist tools.
• Build churn prediction, customer segmentation, and next‑best‑action models.
• Develop demand forecasting models and optimization algorithms for operational efficiency.
• Partner with internal teams to understand business problems and translate them into AI solutions.
• Contribute to the team’s MLOps practices including model versioning, experiment tracking, and automated deployment.

Experience: 3+ years of experience in machine learning, AI engineering, or applied data science. Proven experience deploying ML models into production environments is required.

Technical

Skills:

Strong proficiency in Python and at least one ML framework such as PyTorch, Tensor Flow, scikit‑learn, or Hugging Face. Experience with data pipeline tools and frameworks like Spark, Airflow, dbt, or SQL. Familiarity with cloud platforms (AWS, Azure) and containerized deployment (Docker, Kubernetes).

• Experience in telecommunications, ISP, fiber/broadband, or network‑intensive industries.
• Familiarity with time‑series data, network telemetry, or streaming data platforms.
• Experience with NLP, speech processing, or conversational AI.
• Experience with MLOps tools such as MLflow, Kubeflow, or Weights & Biases.
• Bachelor’s or master’s degree in computer science, Machine Learning, Data Science, or a related field.

We are an equal opportunity employer and welcome applications from all qualified candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.