This role is central to our mission of enhancing everyday intelligence in connected systems. This role will be responsible for building robust pipelines that analyze temporal behavior, identify anomalies, and trigger intelligent alerts.
Job Responsibilities:
- Design, develop, and deploy machine learning models for detecting anomalies in time-series data from connected devices (e.g., cameras, door sensors, access logs).
- Build pipelines that analyze historical patterns and identify deviations using a combination of statistical, classical ML, and deep learning approaches.
- Collaborate with data engineering and platform teams to ensure real-time model inference, stream processing, and alert triggering
- Tune models for low false positives and high sensitivity while maintaining operational efficiency.
- Develop and manage ML Ops pipelines for training, testing, deployment, and monitoring of anomaly detection systems
- Implement robust monitoring and feedback loops to adapt to behavior drift or seasonal variations.
- Contribute to overall AI system architecture and collaborate with engineers working on LLM-based assistants and agentic AI to ensure seamless integration.
- Work across product, engineering, and AI research teams to ensure scalable and performant deployment of models
- Drive decision-making around tooling, infrastructure, observability, and production-readiness.
- Mentor engineers across the org 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 top talent and build a strong, collaborative team culture.
- Comply with health and safety guidelines and rules; managers should also ensure compliance across their teams.
- Protect Chamberlain Group's reputation by keeping information confidential.
- Maintain professional and technical knowledge by attending educational workshops, reading professional publications, establishing personal networks, and participating in professional societies.
- Contribute to the team effort by accomplishing related results and participating on projects as needed.
Job Requirements:
- Bachelor's or Master's degree in Computer Science
- 10+ years of experience software engineering experience with 5+ in ML engineering or data science with a focus 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 (e.g., Prophet, Darts, GluonTS, Kats, Merlion).
- Experience working with event-driven architectures, edge devices, or smart home / IoT environments is a plus.
- Familiarity with vector databases or integration with LLMs
Knowledge, Skills, and Abilities:
- Strong understanding of time-series analysis, including: Trend/seasonality decomposition, Statistical anomaly detection methods (ARIMA, z-score, moving average), Classical ML techniques (Isolation Forest, One-Class SVM, clustering-based approaches), Deep learning for sequences (LSTM, GRU, TCN, Transformers)
- Experience in streaming data processing and building pipelines that operate 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 programming skills in Python and familiarity with ML frameworks (scikit-learn, PyTorch, TensorFlow).
- Proficient in data handling and engineering tools such as Pandas, NumPy, Kafka, Spark, or Flink
Other:
- Ability to travel up to 10% of the time domestically and internationally
Preferred Job Requirements:
- Master's degree in Computer Science, Computer Engineering, or related field
- Experience in IoT, software services, video, and AI
- Analytical and systems thinker who can reason about behavioral patterns over time
- Detail-oriented with a strong focus on data integrity and alert quality
- Comfortable operating in a fast-paced environment and building 0-1 systems
- Effective communicator - able to explain models, metrics, and uncertainty clearly to technical and non-technical stakeholders
- Experience with consumer electronics, smart home companies will be beneficial
The pay range for this position is $148,912.00 - $254,054.00; base pay offered may vary depending on a number of factors including, but not limited to, the position offered, location, education, training, and/or experience. In addition to base pay, also offered is a comprehensive benefits package and 401k contribution (all benefits are subject to eligibility requirements). This position is eligible for participation in a short-term incentive plan subject to the terms of the applicable plans and policies.
