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Home Based Algorithmic Trading Programmer Jobs in California

Senior Software Engineer, Algorithms + ML

Palo Alto, CA · On-site

$144K - $190K/yr

... algorithmic requirements. • Work with platform and domain experts to deploy algorithms into ... trade-offs in a fast-moving product development environment. • Communicate technical findings ...

You will work in a geographically dispersed team alongside experienced traders, quants, data scientists, and engineers, with colleagues based across Europe and the US. Duties * Monitor live sports ...

You will work in a geographically dispersed team alongside experienced traders, quants, data scientists, and engineers, with colleagues based across Europe and the US. Duties * Monitor live sports ...

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological ... Strong understanding of data structures, algorithms, and design principles. * Excellent ...

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Home Based Algorithmic Trading Programmer information

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Infographic showing various Home Based Algorithmic Trading Programmer job openings in California as of July 2026, with employment types broken down into 5% Locum Tenens, 54% As Needed, 23% Full Time, 4% Part Time, 1% Contract, and 13% Nights. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.

Senior Software Engineer, Algorithms + ML

ALSO.

Palo Alto, CA • On-site

$144K - $190K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Job Summary:
ALSO is an electric mobility company focused on creating innovative small EVs to meet global mobility challenges. They are seeking a senior, product-minded Software Engineer with deep experience in algorithms, machine learning, and edge AI to develop and deploy algorithms and ML models across various platforms.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Preferred:
• 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.
Company:
We’re ALSO, an electric mobility company on a mission to build the world’s best small vehicles for moving people and goods, driven and autonomous. Founded in 2025, the company is headquartered in Palo Alto, USA, with a team of 201-500 employees. The company is currently Growth Stage.