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Bosch Machine Learning Jobs in California (NOW HIRING)

PlusAI

Machine Learning Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

... Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation ... Machine Learning & NLP: Solid understanding of Large Language Models (LLMs), natural language ...

PlusAI

Machine Learning Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

... Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation ... Machine Learning & NLP: Solid understanding of Large Language Models (LLMs), natural language ...

Bosch Group

Wireless Sensing Research Intern

Sunnyvale, CA · On-site

$32 - $69/hr

Experienced in using different machine learning libraries and tools (e.g. TensorFlow) * Strong C ... Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent ...

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Bosch Machine Learning information

What are the key skills and qualifications needed to thrive as a Bosch Machine Learning Engineer, and why are they important?

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 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 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 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.
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Bosch Machine Learning jobs near you
Machine Learning Audio Intern

Machine Learning Audio Intern

Syntiant

Redwood City, CA • On-site

Temporary

Posted 10 days ago

Job description

Summary Description:

Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey Gobble Synthesis.

Syntiant Corp. is seeking a turkey gobble detector AED model that runs on NDP chips. It is difficult to collect good quality gobble data due to several logistical issues. As of now, only ~2K samples are available for training such a model. These samples are not enough to train a production quality turkey gobble model.

EcoGen is a neural network model that could generate synthetic but real-sounding bird sounds. It needs only a handful of recordings to synthesize similar sounds. The idea is to leverage this model to get more data for training a better turkey gobble detector AEDmodel. For details on EcoGen, please refer to the hyperlink provided. There are newer models such as BirdDiff, Audio LDM (Text-to-Turkey), Perch 2.0 etc.

Requirements

Specific Duties and Responsibilities:

  • Understanding the model architecture.
  • Running it locally or on the cluster.
  • Fine-tuning the model on the available turkey sounds.
  • Synthesizing real-sounding artificial turkey gobble sounds.
  • Explore better alternatives and pursue them.

Qualifications, Education, and Experience Required:

  • Candidate pursuing a Bachelor's or Master's degree in Computer Science or related field with hands-on experience in AI/ML model training.
  • Industry work experience is not required, but it would be good to have.

Benefits

About Syntiant:

Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering hardware and software solutions for edge AI deployment. The company's purpose-built silicon and hardware-agnostic models are being deployed globally to power edge AI speech, audio, sensor and vision applications across a wide range of consumer and industrial use cases, from earbuds to automobiles. Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient software solutions with proprietary model architectures that enable world-leading inference speed and minimized memory footprint across a broad range of processors. The company is backed by several of the world's leading strategic and financial investors including Intel Capital, Microsoft's M12, Applied Ventures, Bosch Ventures, the Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by visiting www.syntiant.com.

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