Staff Software Engineer - ML/AI

Chamberlain Group • Oak Brook, IL

20h • $148,912 - $254,054

About The Position

Chamberlain Group is hiring a Staff Software Engineer - ML/AI to build machine learning systems that analyze temporal behavior in connected devices, detect anomalies, and trigger intelligent alerts. The role focuses on production-ready anomaly detection across time-series data from sources such as cameras, door sensors, and access logs, while contributing to the broader AI system architecture and integration with LLM-based assistants and agentic AI.

The position works across data engineering, platform, product, engineering, and AI research teams to deploy scalable, performant models. It also provides technical leadership by guiding decisions about tooling, infrastructure, observability, and production readiness, mentoring engineers in AI-native engineering and the LLM ecosystem, and managing and growing a team of applied AI and full-stack engineers. The role includes hiring, career development, and building a collaborative team culture.

The employee must comply with health and safety guidelines, protect confidential information, maintain professional and technical knowledge, and contribute to team projects as needed. Domestic and international travel of up to 10% is required. The advertised pay range is $148,912 to $254,054, with pay varying based on factors such as position, location, education, training, and experience. The position is eligible for a short-term incentive plan and includes a comprehensive benefits package and 401(k) contribution, subject to eligibility and plan terms.

Requirements

• Bachelor’s or master’s degree in Computer Science.
• 10+ years of software engineering experience, including 5+ years in ML engineering or data science focused on real-time systems, behavior modeling, or time-series data.
• Proven experience building and deploying anomaly detection systems in production.
• Hands-on experience with time-series libraries such as Prophet, Darts, GluonTS, Kats, or Merlion.
• Strong understanding of time-series analysis, including trend and seasonality decomposition; statistical anomaly detection methods such as ARIMA, z-score, and moving average; classical ML techniques such as Isolation Forest, One-Class SVM, and clustering-based approaches; and deep learning for sequences such as LSTM, GRU, TCN, and Transformers.
• Experience in streaming data processing and building pipelines operating on live or near-real-time data.
• Knowledge of change point detection, event modeling, and alert systems.
• Ability to design interpretable anomaly detection systems with threshold tuning, confidence scoring, and alert escalation.
• Understanding of MLOps principles, including CI/CD for ML, versioning, and retraining strategies.
• Strong Python programming skills and familiarity with ML frameworks such as scikit-learn, PyTorch, and TensorFlow.
• Proficiency with data handling and engineering tools such as Pandas, NumPy, Kafka, Spark, or Flink.
• Ability to travel up to 10% domestically and internationally.

Nice To Haves

• Experience with event-driven architectures, edge devices, or smart home/IoT environments.
• Familiarity with vector databases or integration with LLMs.
• Master’s degree in Computer Science, Computer Engineering, or a related field.
• Experience in IoT, software services, video, and AI.
• Analytical and systems-thinking ability to reason about behavioral patterns over time.
• Detail-oriented approach with a strong focus on data integrity and alert quality.
• Comfort operating in a fast-paced environment and building 0-to-1 systems.
• Effective communication skills, including explaining models, metrics, and uncertainty to technical and non-technical stakeholders.
• Experience with consumer electronics or smart home companies.

Responsibilities

• Design, develop, and deploy machine learning models to detect anomalies in time-series data from connected devices, including cameras, door sensors, and access logs.
• Build pipelines that analyze historical patterns and identify deviations using statistical, classical machine learning, and deep learning approaches.
• Collaborate with data engineering and platform teams to support real-time model inference, stream processing, and alert triggering.
• Tune models to reduce false positives and maintain high sensitivity and operational efficiency.
• Develop and manage MLOps pipelines for training, testing, deployment, and monitoring of anomaly detection systems.
• Implement monitoring and feedback loops to adapt to behavior drift and seasonal variations.
• Contribute to AI system architecture and collaborate with engineers working on LLM-based assistants and agentic AI to support seamless integration.
• Work across product, engineering, and AI research teams to ensure scalable and performant model deployment.
• Drive decisions about tooling, infrastructure, observability, and production readiness.
• Mentor engineers in AI-native engineering patterns, architecture, and developments in the LLM ecosystem.
• Manage, mentor, and grow a team of applied AI and full-stack engineers; guide career development, hire talent, and build a collaborative team culture.
• Comply with health and safety guidelines and rules, and ensure team compliance as a manager.
• Protect Chamberlain Group’s reputation by keeping information confidential.
• Maintain professional and technical knowledge through educational workshops, professional publications, personal networks, and professional societies.
• Contribute to team efforts by completing related work and participating in projects as needed.

Benefits

• Comprehensive benefits package.
• 401(k) contribution.
• Eligibility to participate in a short-term incentive plan, subject to applicable plan terms and policies.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior