Machine Learning Engineer
Cupertino, CA · On-site
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...
Machine Learning Engineer
Cupertino, CA · On-site
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...
As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with ...
As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with ...
Senior Machine Learning Engineer
San Francisco, CA · Hybrid
$144.30K - $190.30K/yr
Reports to: Manager, Machine Learning Engineering * Collaborate with scientists and product ... Experience with LLMOps - evaluation, monitoring, quantization, teacher-learner, etc.). * Hands-on ...
Senior Machine Learning Engineer
San Francisco, CA · Hybrid
$144.30K - $190.30K/yr
Reports to: Manager, Machine Learning Engineering * Collaborate with scientists and product ... Experience with LLMOps - evaluation, monitoring, quantization, teacher-learner, etc.). * Hands-on ...
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data ...
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data ...
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data ...
We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data ...
As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with ...
As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with ...
Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for millions of users ...
Are you a passionate Machine Learning Engineer with a deep love for photography? Join Apple's Camera Hardware Engineering team and help us redefine the camera experience for millions of users ...
Machine Learning Engineer
Los Angeles, CA · On-site
The Senior Machine Learning Engineer will be responsible for designing, building, and scaling advanced software systems to automate Design for Manufacturing analysis, utilizing deep learning models ...
Machine Learning Engineer
Los Angeles, CA · On-site
The Senior Machine Learning Engineer will be responsible for designing, building, and scaling advanced software systems to automate Design for Manufacturing analysis, utilizing deep learning models ...
Machine Learning Engineer Only on W2 Duration: 12 months Location: Mountain View, CA (Local candidates Required) Position Summary We are looking for an experienced Machine Learning Engineer to lead ...
Machine Learning Engineer Only on W2 Duration: 12 months Location: Mountain View, CA (Local candidates Required) Position Summary We are looking for an experienced Machine Learning Engineer to lead ...
They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.
They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to core technology and product features.
The Modem Machine Learning Engineer applies advanced machine learning techniques to next-generation ... Exposure to on-device ML deployment, quantization, and neural network optimization tools.
The Modem Machine Learning Engineer applies advanced machine learning techniques to next-generation ... Exposure to on-device ML deployment, quantization, and neural network optimization tools.
Machine Learning Engineer
San Francisco, CA · On-site
$130K - $170K/yr
Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish farms across the world. You'll be responsible for software and machine learning model development of ...
Machine Learning Engineer
San Francisco, CA · On-site
$130K - $170K/yr
Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish farms across the world. You'll be responsible for software and machine learning model development of ...
Machine Learning Engineer
San Mateo, CA · On-site
Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...
Machine Learning Engineer
San Mateo, CA · On-site
Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...
The Role As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world ...
Quick apply
The Role As a Machine Learning Engineer at the Institute of Foundation Models, your primary responsibility is to develop and implement innovative machine learning models that address real-world ...
Machine Learning Engineer
Fremont, CA · On-site
They are seeking a highly motivated Machine Learning Engineer to design and implement machine learning models for advanced battery products, collaborating with cross-disciplinary teams to address ...
Machine Learning Engineer
Fremont, CA · On-site
They are seeking a highly motivated Machine Learning Engineer to design and implement machine learning models for advanced battery products, collaborating with cross-disciplinary teams to address ...
Machine Learning Engineer
San Francisco, CA · On-site
$225K - $300K/yr
Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...
Machine Learning Engineer
San Francisco, CA · On-site
$225K - $300K/yr
Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...
Sr. Staff Engineer, Machine Learning Engineering (Quantization SW)
San Diego, CA · On-site
$110.90K - $152.40K/yr
Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Artificial ... Prior experience with model quantization, profiling and running models on edge devices. * Prior ...
Sr. Staff Engineer, Machine Learning Engineering (Quantization SW)
San Diego, CA · On-site
$110.90K - $152.40K/yr
Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Artificial ... Prior experience with model quantization, profiling and running models on edge devices. * Prior ...
Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...
Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...
BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...
BeeGenius is building the future of work, and they are seeking an AI/Machine Learning Engineer to join their team. In this role, you will be responsible for developing and implementing machine ...
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...
Quick apply
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...
Machine Learning Engineer Quantization information
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Quantization, and why are they important?
To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.
What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?
Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.
What does a Machine Learning Engineer Quantization do?
A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.
What is the difference between Machine Learning Engineer Quantization vs Data Scientist?
| Aspect | Machine Learning Engineer Quantization | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or master's in CS, ML, or related; certifications in ML or AI | Bachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics |
| Work Environment | Developing optimized ML models, deploying quantized models for efficiency | Analyzing data, building predictive models, interpreting results |
| Industry Usage | Tech companies, AI hardware firms, embedded systems | Finance, healthcare, marketing, research institutions |
Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.
What are popular job titles related to Machine Learning Engineer Quantization jobs in California? For Machine Learning Engineer Quantization jobs in California, the most frequently searched job titles are:
- Flexible Machine Learning Engineer Biotech
- Machine Learning Engineer
- Staff Software Engineer Machine Learning
- Google Cloud Machine Learning Engineer
- Lead Machine Learning Engineer
- Machine Learning Consultant
- Machine Learning Engineer New Grad
- Volunteer Junior Machine Learning Engineer
- Manager Remote Machine Learning Engineer
- Remote Senior Machine Learning Engineer
What job categories do people searching Machine Learning Engineer Quantization jobs in California look for? The top searched job categories for Machine Learning Engineer Quantization jobs in California are:
What cities in California are hiring for Machine Learning Engineer Quantization jobs? Cities in California with the most Machine Learning Engineer Quantization job openings:
Apple rating
8.1
Based on 661 frontline employees who took The Breakroom Quiz
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Job description
As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine learning solutions from research and experimentation through to robust, production-grade deployment.
The MLE will collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. This hire will design end-to-end AI/ML solutions with clear business impact, from concept to deployment, with a strong focus on feasibility, scalability, and performance. You will benchmark, adapt, and integrate AI/ML models into existing systems.
8 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.Bachelor's Degree in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field.Proficiency in one or more object-oriented programming languages such as Python, Java, or C++, with hands-on experience building distributed systems.Experience building large-scale machine learning systems using big data technologies such as Spark, SQL, Snowflake, or similar platforms.Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.Familiarity with MLOps practices including model versioning, CI/CD pipelines, and experiment tracking tools such as MLflow or similar.Experience building and deploying applications using large language models (e.g., GPT-4, Claude, Gemini, or open-source alternatives) via APIs or self-hosted inference.Hands-on experience with agentic frameworks such as LangChain, LlamaIndex, or AutoGen to build multi-step, tool-augmented AI workflows.
10 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.Solid understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.Strong problem-solving skills with the ability to translate ambiguous business problems into well-defined ML solutions.Excellent cross-functional communication skills with the ability to collaborate effectively across engineering and data science teams.Familiarity with LLM evaluation practices including output quality assessment, hallucination detection, and latency benchmarking in production environments.
The MLE will collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. This hire will design end-to-end AI/ML solutions with clear business impact, from concept to deployment, with a strong focus on feasibility, scalability, and performance. You will benchmark, adapt, and integrate AI/ML models into existing systems.
8 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.Bachelor's Degree in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field.Proficiency in one or more object-oriented programming languages such as Python, Java, or C++, with hands-on experience building distributed systems.Experience building large-scale machine learning systems using big data technologies such as Spark, SQL, Snowflake, or similar platforms.Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.Familiarity with MLOps practices including model versioning, CI/CD pipelines, and experiment tracking tools such as MLflow or similar.Experience building and deploying applications using large language models (e.g., GPT-4, Claude, Gemini, or open-source alternatives) via APIs or self-hosted inference.Hands-on experience with agentic frameworks such as LangChain, LlamaIndex, or AutoGen to build multi-step, tool-augmented AI workflows.
10 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.Solid understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.Strong problem-solving skills with the ability to translate ambiguous business problems into well-defined ML solutions.Excellent cross-functional communication skills with the ability to collaborate effectively across engineering and data science teams.Familiarity with LLM evaluation practices including output quality assessment, hallucination detection, and latency benchmarking in production environments.
About Apple
Sourced by ZipRecruiter
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Cupertino, CA, US
Year founded
1976