Staff ML Engineer: Real-Time Anomaly Detection & IoT

Chamberlain Group; Oak Brook (IL); On-site; USD 149,000 - 254,000; Full time

Benefits offered by this job

Benefits package

401(k) plan

Short-term incentive plan

Job summary

Chamberlain Group is seeking a senior ML engineer to design and deploy anomaly-detection systems for real-time time-series data from IoT devices. You will build end-to-end pipelines, experiment with statistical and deep-learning approaches, and collaborate across data, product, and engineering teams to deliver scalable AI solutions.

The role emphasizes MLOps, monitoring, and production readiness, with travel up to 10%. Come join a team shaping intelligent access at scale.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field is required.
• 10+ years of software engineering with 5+ years in ML engineering or data science focusing on real-time systems.
• Proven experience deploying anomaly detection in production and familiar with time-series libraries.
• Experience with event-driven architectures, IoT environments, and familiarity with vector databases/LLMs.

Responsibilities

• Design, develop, and deploy ML models for anomaly detection in time-series data from connected devices.
• Build pipelines analyzing historical patterns to detect deviations using statistical, classical ML, and deep learning methods.
• Collaborate with data engineering and platform teams to enable real-time inference and alerting.
• Develop and manage MLOps pipelines for training, testing, deployment, and monitoring.

Skills

Python programming

Time-series analysis

MLOps

Statistical anomaly detection

Deep learning for sequences

Communication

Analytics

IoT / edge

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Prophet

Darts

GluonTS

Kats

Merlion

scikit-learn

PyTorch

TensorFlow

Pandas

NumPy

Kafka

Spark

Flink

Job description

Chamberlain Group is seeking a senior ML engineer to design and deploy anomaly-detection systems for real-time time-series data from IoT devices. You will build end-to-end pipelines, experiment with statistical and deep-learning approaches, and collaborate across data, product, and engineering teams to deliver scalable AI solutions.

The role emphasizes MLOps, monitoring, and production readiness, with travel up to 10%. Come join a team shaping intelligent access at scale.