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Mid Level Machine Learning Teaching Jobs in California

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others * You know the ins and outs of Python, especially as it ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others * You know the ins and outs of Python, especially as it ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Design tools and interfaces for interactive machine learning and teaching. * Research and development on cutting-edge machine learning technologies. Qualifications and Skills: * Graduate degree in ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Design tools and interfaces for interactive machine learning and teaching. * Research and development on cutting-edge machine learning technologies. Qualifications and Skills: * Graduate degree in ...

Ema

Software Engineer, Machine Learning

Bodega Bay, CA · On-site

$160K - $220K/yr

At least 2 years of industry experience in building and deploying production-level machine learning models. * Deep understanding and practical experience with NLP techniques and frameworks, including ...

Ema

Software Engineer, Machine Learning

San Francisco, CA · On-site

$160K - $220K/yr

At least 2 years of industry experience in building and deploying production-level machine learning models. * Deep understanding and practical experience with NLP techniques and frameworks, including ...

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Mid Level Machine Learning Teaching information

What is the difference between Mid Level Machine Learning Teaching vs Data Scientist?

AspectMid Level Machine Learning TeachingData Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related; teaching experienceBachelor's or Master's in CS, Data Science, or related; often requires experience
Work EnvironmentEducational institutions, online platforms, corporate trainingTech companies, finance, healthcare, research labs
Employer & Industry UsageEducational and training sectors, universities, online educationPrivate sector, industry-specific applications, research
Common Search & Comparison IntentUnderstanding teaching roles in ML, educational careersData analysis, modeling, industry applications

Mid Level Machine Learning Teaching focuses on educating students or professionals in ML concepts, often requiring teaching experience and educational credentials. Data Scientists analyze data, build models, and apply ML techniques in industry settings. While both roles involve ML knowledge, teaching emphasizes instruction, whereas data science emphasizes application and analysis.

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The most popular types of Machine Learning Teaching jobs in California are:

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For Mid Level Machine Learning Teaching jobs in California, the most frequently searched job titles are:

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Cities in California with the most Mid Level Machine Learning Teaching job openings:

Mid Level Machine Learning Teaching jobs near you
Infographic showing various Mid Level Machine Learning Teaching job openings in California as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Mid-Level Machine Learning Engineer

TetraMem - Accelerate The World

San Jose, CA • On-site

Full-time

Re-posted 4 days ago

Job description

Job Summary:
TetraMem is a company focused on accelerating the world through innovative technology, and they are seeking a Mid-Level Machine Learning Engineer to develop and optimize machine learning models for edge AI applications. The role involves collaborating with hardware and software teams, providing mentorship, and researching state-of-the-art ML techniques to enhance model efficiency.
Responsibilities:
• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Work closely with hardware and software teams to integrate ML models into production systems.
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
• Provide technical leadership and mentorship to junior engineers.
• Publish research findings, present at conferences, and contribute to open-source projects when applicable.
Qualifications:
Required:
• 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
• Strong experience in machine learning, with a focus on edge AI and lightweight model deployment.
• Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.
• Proficiency in programming languages such as C/C++, Python, and experience with ML model optimization.
• Ability to work independently and collaboratively in a fast-paced startup environment.
• Ability to provide mentorship, technical guidance, and career development support to junior engineers and interns.
Preferred:
• Understanding of ML compiler and runtime design.
• Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
• Familiarity with hardware acceleration techniques.
• Experience in embedded system development.
Company:
TetraMem is developing cutting-edge analog computing solutions for AI applications, offering exceptional performance with ultra-low power consumption. Founded in 2018, the company is headquartered in Newark, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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