Staff Software Engineer - ML/AI
About The Position
Chamberlain Group is hiring a Staff Software Engineer - ML/AI to build intelligent systems that analyze temporal behavior, identify anomalies, and trigger alerts. The role focuses on developing and deploying machine-learning models and pipelines for time-series data from connected devices, including cameras, door sensors, and access logs. It involves real-time inference, stream processing, model monitoring, and operationalizing anomaly detection systems. The engineer will contribute to AI system architecture and work with product, engineering, data engineering, platform, and AI research teams. The role also includes making decisions about tooling, infrastructure, observability, and production readiness; mentoring engineers in AI-native engineering patterns and the LLM ecosystem; and managing, mentoring, and growing a team of applied AI and full-stack engineers. The position requires compliance with health and safety guidelines, maintaining confidentiality, professional development, and participation in team projects as needed. Domestic and international travel may be required, up to 10% of the time.
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; and sequence deep-learning approaches such as LSTM, GRU, TCN, and Transformers.
- Experience with streaming data processing and 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 ML CI/CD, versioning, and retraining strategies.
- Strong Python programming skills and familiarity with 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.
- Ability to reason analytically 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.
- 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 enable 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.
- Work across product, engineering, and AI research teams to support scalable and performant model deployment.
- Drive decisions about tooling, infrastructure, observability, and production readiness.
- Mentor engineers in AI-native engineering patterns, architecture, and LLM ecosystem evolution.
- 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 ensure team compliance.
- Protect confidential information and Chamberlain Group’s reputation.
- Maintain professional and technical knowledge through educational workshops, professional publications, networking, and professional societies.
- Contribute to team efforts by completing related work and participating in projects as needed.
Benefits
- Comprehensive benefits package, subject to eligibility requirements.
- 401k contribution, subject to eligibility requirements.
- Eligibility to participate in a short-term incentive plan, subject to applicable plan terms and policies.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
