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Machine Learning Engineer Quantization Jobs in Idaho

SwiftCruit

Machine Learning Engineer

Boise, ID · On-site

$110 - $150/hr

  • Medical

  • Retirement

  • PTO

As a Machine Learning Engineer in the Identity and Fraud business at Equifax, you will solve challenging technology problems and build architecturally sound, high-quality software that moves data ...

Micron Technology

Staff Machine Learning Engineer

Boise, ID · On-site

$120 - $150/hr

  • Medical

  • Dental

  • Vision

  • PTO

JR101366 Staff Machine Learning Engineer Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage ...

Micron Technology

Staff Machine Learning Engineer

Boise, ID · On-site

  • Medical

  • Dental

  • Vision

  • PTO

The Smart Manufacturing and AI team at Micron Technology is looking for an ambitious Machine Learning Engineer. Are you curious, high velocity, and ready to solve complex problems? Do you dream in ...

Micron

Principal Machine Learning Engineer

Boise, ID · On-site

  • Medical

  • Dental

  • Vision

  • PTO

As a Principal Machine Learning Engineer, willhave experiencein a variety of dataand cloudtechnologies and have extensive practice modeling data, querying, anddeployingscalable pipelinestoexecute ...

New

Bespoke Labs

Machine Learning Engineer

Meridian, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Boise, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Rexburg, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Pocatello, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Moscow, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Nampa, ID · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Machine Learning Engineer Quantization information

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 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 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?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, 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 Idaho? For Machine Learning Engineer Quantization jobs in Idaho, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Idaho look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Idaho are:
What cities in Idaho are hiring for Machine Learning Engineer Quantization jobs? Cities in Idaho with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

SwiftCruit

Boise, ID • On-site

$110 - $150/hr

Other

Medical, Retirement, PTO

Posted 7 days ago

Job description

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you.

This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support.

As a Machine Learning Engineer in the Identity and Fraud business at Equifax, you will solve challenging technology problems and build architecturally sound, high-quality software that moves data through models to make automated decisions. You will achieve success through communicating, collaborating, and developing creative and performant solutions to help Equifax provide certainty in every digital transaction for our customers. You should be a creative, driven, motivated engineer that can think outside the box, have the ability to learn quickly, and can deliver high-quality working solutions that are both maintainable and scalable. You will work with data scientists to develop requirements for novel algorithms, and with operations and other developers to bring data transformation pipelines and machine learning models to practice.

What you’ll do
  • Design platforms and pipelines for researching, developing, and running machine learning models
  • Productionize machine learning models by building performant data transformations, storage, and pipelines
  • Develop and maintain microservices that serve data, model features, and scores to other internal services, as well as external customers
  • Demonstrate effective, respectful, and honest communication when collaborating with colleagues including a cross‑functional team consisting of Data Science, Operations, and Engineering
  • Apply development and testing best practices (including unit, service, and integration tests) and demonstrate excellent software craftsmanship to produce maintainable, scalable, and quality solutions.
  • Contribute to all phases of product development and delivery from Analysis & Design all the way through to successful Deployment.
  • Deliver on company initiatives and projects prioritized for your team and support long term technical vision.
  • Collaborate with the product team, architects, and others to document features and changes.
  • Identify gaps and iterative improvements to legacy model platforms, frameworks, or governance stacks
  • Adhere to and influence best practices (i.e. security, architecture, platform, etc.)
  • Participate in peer design and code reviews
  • Participate in on-call rotation with other engineers
What experience you need
  • BS in Computer Science, Engineering, or equivalent experience.
  • 3+ years of strong software engineering and software architecture background using languages such as Golang, Python, and SQL.
  • 3+ years of experience building RESTful APIs and/or gRPC within a distributed microservice architecture.
  • 2+ years of experience implementing Amazon Web Services (e.g., IAM, Lambda, EKS, Neptune, DynamoDB, RDS).
  • 2+ years of experience using IaC tooling such as Terraform
  • Experience working with machine learning frameworks such as SparkMLlib, Scikit-Learn, MLflow, or TensorFlow.
  • Experience serving ML model inference at scale in low‑latency (<30ms) environments.
  • Experience with metrics, logging, and evaluating model performance (e.g., DataDog, evaluation latency, and ROC curves).
What could set you apart
  • Experience with Snowflake
  • Experience with AWS EMR
  • Experience deploying diverse model architectures into production using portable formats like ONNX or MLeap.

We offer comprehensive compensation and healthcare packages, 401k matching, paid time off, and organizational growth potential through our online learning platform with guided career tracks.

Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference!

Primary Location:

USA-ID-Boise

Function:

Function - Tech Dev and Client Services

Schedule:

Full time

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