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Bosch Machine Learning Jobs in California (NOW HIRING)

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Bosch Machine Learning information

What is a Bosch machine learning engineer?

A Bosch Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for Bosch’s products and services. These engineers work on projects involving data analysis, pattern recognition, and artificial intelligence to improve automation, predictive maintenance, and smart features in Bosch's automotive, industrial, and consumer goods divisions. They collaborate with software developers, data scientists, and product teams to integrate intelligent solutions into real-world applications, ensuring efficiency and innovation across Bosch’s technology portfolio.

What are the key skills and qualifications needed to thrive as a Bosch machine learning engineer?

To thrive as a Bosch Machine Learning Engineer, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by a relevant degree. Familiarity with Python, TensorFlow, PyTorch, and Bosch-specific tools or platforms is commonly required, along with experience in deploying models on embedded or edge devices. Strong problem-solving skills, collaboration, and clear communication set candidates apart in this role. These skills and qualities are crucial for designing effective AI solutions that integrate seamlessly with Bosch's products and drive innovation.

What are some common challenges faced by machine learning engineers at Bosch, and how can applicants prepare for them?

Machine learning engineers at Bosch often work with large-scale, real-world datasets, which can be noisy and require significant preprocessing. Balancing the integration of new ML solutions into legacy industrial systems is another frequent challenge, demanding both technical proficiency and adaptability. To prepare, applicants should strengthen their skills in data cleaning, feature engineering, and deployment of models in production environments, as well as develop a solid understanding of Bosch’s domain-specific applications like manufacturing or automotive. Collaboration with multidisciplinary teams is also common, so strong communication skills are highly beneficial.

What is the difference between Bosch Machine Learning vs Bosch Data Scientist?

AspectBosch Machine LearningBosch Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related field; experience in ML algorithmsDegree in Statistics, Data Science, or related; strong programming skills
Work EnvironmentDeveloping ML models for products and automation systemsAnalyzing data, building predictive models, and providing insights
Employer & Industry UsageApplied in manufacturing, automotive, and IoT sectorsUsed across R&D, product development, and analytics teams

While both roles involve data and algorithms, Bosch Machine Learning focuses on developing and deploying machine learning models, whereas Bosch Data Scientists analyze data to generate insights and support decision-making. Both roles are integral to Bosch's innovation in technology and automation.

What are popular job titles related to Bosch Machine Learning jobs in California?

For Bosch Machine Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Bosch Machine Learning jobs in California look for?

The top searched job categories for Bosch Machine Learning jobs in California are:

Bosch Machine Learning jobs near you
Infographic showing various Bosch Machine Learning job openings in California as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.

Senior Machine Learning Infrastructure Engineer

Santa Clara, CA • On-site, Remote

PlusAI
See more jobs at PlusAIexternal

$160K - $200K/yr

Full-time

Retirement

Re-posted 10 days ago

Job description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World's Most Innovative Companies. Partners including TRATON GROUP's Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you're ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.

As a Senior ML Infrastructure Engineer at Plus, you will design scalable architectures capable of handling petabytes of data while ensuring optimal performance for both training and inference phases. You will build robust pipelines for managing model versioning systems and experiment tracking frameworks, which are essential for maintaining reproducibility across experiments. Additionally, you will be responsible for managing large-scale GPU clusters. This role offers unparalleled opportunities-both technically and professionally-for individuals passionate about solving challenging problems using modern cloud-native technologies. Ideal candidates thrive in environments that leverage tools such as Docker containers orchestrated via Kubernetes clusters, seamlessly integrated with state-of-the-art deep learning frameworks like PyTorch or TensorFlow. If you are eager to push the boundaries of what's possible in machine learning infrastructure and contribute to cutting-edge solutions, this position is an excellent fit!
Responsibilities:
  • Design and develop scalable, high-performance systems for training, inference, deploying, and monitoring ML models at scale.
  • Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks.
  • Collaborate with cross-functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability.
  • Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure.
  • Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems.
  • Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform.
  • Mentor junior engineers and contribute to a culture of technical excellence
  • Ensure that your work is performed in accordance with the company's Quality Management System (QMS) requirements and contribute to continuous improvement efforts.
  • Ensure team compliance with QMS, monitor quality, and drive process improvements.
Required Skills:
  • Phd or MS in Computer Science, Electrical Engineering, or related field
  • Good oral and written communication skills
  • Phd new grad or Masters with 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems.
  • Proficiency in in Python, C++, SQL
  • Deep understanding of containerization, orchestration technologies, distributed ML workload, and experiment tracking tools (e.g., Docker, Kubernetes, multiprocessing, Kubeflow, and mlflow)
  • Deploy and manage resources across multiple cloud platforms (AWS, GCP, or on-prem environments)
  • Proficiency in at least one deep learning framework, such as PyTorch and data pipeline tools (e.g., Apache Airflow, Prefect).
  • Strong knowledge of distributed systems, databases, and storage solutions.
  • Extensive software design and development skills.
  • Ability to learn and adapt to new technologies and contribute in a productive environment.
Preferred Skills:
  • Familiarity with fundamental deep learning architectures, such as Convolutional Neural Networks (CNNs) and Transformer models
  • Experience in building large-scale ML datasets, MLOps pipelines, and distributed computing frameworks like Ray
  • Experience working with autonomous vehicles or robotics
 
Salary Range:
  • $160,000 - $200,000 a year
Our compensations (cash and equity) are determined based on the position, your location, qualifications, and experience.

Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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