Senior Software Engineer, Algorithms + ML
- Design, develop, deploy, and iterate on algorithms and ML models across mobile, embedded, and cloud platforms.
- Partner with Product Managers, Designers, and Engineering stakeholders to translate customer needs into clear algorithmic requirements.
- Work with platform and domain experts to deploy algorithms into production and monitor their behavior in real-world environments.
- Analyze model and algorithm performance using experimentation, A/B testing, shadow testing, telemetry analysis, and offline evaluation.
- Design and maintain input/output data schemas to support efficient edge-to-cloud telemetry, diagnostics, model retraining, and continuous improvement.
- Optimize deployed algorithms for latency, battery usage, communication efficiency, robustness, and intended product behavior.
- Identify and investigate outliers, failure modes, regressions, and edge cases in production data.
- Use real-world telemetry data and generate synthetic data where needed for training, testing, validation, and simulation.
- Build processes to monitor model performance, data drift, model drift, and concept drift over time.
- Collaborate with Cloud and Data Engineering teams on data pipelines that support model development, validation, deployment, and retraining.
- Support algorithms used in customer-facing products as well as factory, manufacturing, and validation workflows.
- Manage technical priorities, project timelines, and trade-offs in a fast-moving product development environment.
- Communicate technical findings, performance trends, and improvement plans clearly to technical and non-technical stakeholders.
- 5+ years of professional experience building algorithms, ML systems, or production software for mobile, embedded, cloud, or connected products.
- A track record of shipping algorithms or ML models into production, ideally on resource-constrained devices, mobile applications, embedded systems, or cloud-connected products.
- Strong hands-on programming skills in Python and C/C++, with the ability to write production-quality, testable, and maintainable code.
- Data manipulation with SQL and knowledge of Data Warehousing solutions like DataBricks or Snowflake.
- Practical knowledge of algorithm development, model building, or signal-processing workflows using tools such as MATLAB, NumPy, SciPy, PyTorch, TensorFlow, or similar frameworks.
- Familiarity deploying models or algorithms to edge environments using tools such as TensorFlow Lite, Edge Impulse, PyTorch Mobile, ExecuTorch, or comparable edge deployment frameworks.
- Demonstrated ability to optimize deployed algorithms against real-world constraints such as latency, battery life, compute usage, memory footprint, bandwidth, reliability, and product behavior.
- Comfort working with telemetry, logs, device data, and production performance data to diagnose issues, measure outcomes, identify outliers, and improve algorithm performance over time.
- Hands-on involvement with data schemas, data pipelines, or edge-to-cloud telemetry flows that support model validation, monitoring, retraining, diagnostics, or experimentation.
- Working knowledge of experimentation methods such as A/B testing, shadow testing, offline evaluation, simulation, synthetic data generation, and production monitoring.
- Familiarity with CI/CD pipelines, Docker, automated testing, and MLOps or model deployment workflows.
- Domain knowledge in one or more areas such as mobility, IoT, automotive, fitness, wearables, robotics, consumer electronics, or connected devices.
- The ability to collaborate with Embedded, Mobile, Cloud, Data, Product, Design, Manufacturing, and Systems Engineering teams to make practical technical trade-offs.
- Clear communication skills, including the ability to explain algorithm behavior, performance trends, trade-offs, risks, and recommendations to technical and non-technical stakeholders.
- Exposure to real-time operating systems, embedded Linux, iOS, Android, hardware-in-the-loop systems, simulation environments, factory production, or manufacturing validation workflows is a plus.
- Robust health coverage. Excellent health, dental and vision insurance covered up to 100% by Also. with FSA & HSA options.
- One Medical membership and dedicated insurance advocates.
- Rich fertility and family building benefits with Progyny.
- Flexible time off.
- 401(k) match.
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