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Machine Learning Engineer Quantization Jobs in Minnesota

York Solutions, LLC

ML Engineer

Saint Paul, MN · On-site +1

AI Center of Excellence as a Machine Learning Engineer Consultant! In this exciting role, you?ll collaborate with talented experts to build innovative solutions that address our company?s evolving ...

NxT Level

Principal AI / ML Engineer

Minneapolis, MN · On-site

We're looking for a Principal Machine Learning Engineer to build AI features for the family. Qualifications: * A confident craftsperson who possesses problem-solving tools and can discuss multiple ...

Deloitte

AI Solutions Architect

Minneapolis, MN

$65.75 - $86.75/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

AI Data Engineer - Manager

Minneapolis, MN · On-site

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

Deloitte

AI Data Engineer Manager

Minneapolis, MN · On-site

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

UnitedHealth Group

Lead AI/ML Engineer - Remote

Eden Prairie, MN · On-site +1

$104.50K - $137.60K/yr

Build machine learning models; perform proof-of-concept experiments; optimize and deploy models to production; partner with software engineers to productionize ML models * Perform hands-on analysis ...

UnitedHealth Group

Lead AI/ML Engineer - Remote

Eden Prairie, MN · On-site +1

$104.50K - $137.60K/yr

Build machine learning models; perform proof-of-concept experiments; optimize and deploy models to production; partner with software engineers to productionize ML models * Perform hands-on analysis ...

Countryfinancial

Data Scientist Sr

Minneapolis, MN · On-site

$108.80K - $149.60K/yr

Key Responsibilities: -Build and maintain robust Machine Learning (ML) and Artificial Intelligence (AI) models and deployment environments -Drive activities with a special focus on model engineering ...

Deloitte

Senior AI Engineer - SFL Scientific

Minneapolis, MN

$109.10K - $149.80K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Autodesk

Report: You will report to the Machine Learning Manager in the Architecture, Engineering, and Construction (AEC) Solutions Team. Location: We support hybrid work, and you work near our Boston ...

Vizient, Inc.

Associate AI/ML Engineer

Edina, MN · On-site

$68.50K - $116.30K/yr

In this role, you will develop and support machine learning and data-driven solutions that address ... Collaborate with data engineers, analysts, and clients to translate business requirements into ...

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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?

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 Minnesota? For Machine Learning Engineer Quantization jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Minnesota look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Minnesota are:
What cities in Minnesota are hiring for Machine Learning Engineer Quantization jobs? Cities in Minnesota with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
ML Engineer

ML Engineer

York Solutions, LLC

Saint Paul, MN • On-site, Remote

Other

Medical, Dental, Vision, Life, Retirement

Posted yesterday

Job description


AI Center of Excellence as a Machine Learning Engineer Consultant! In this exciting role, you?ll collaborate with talented experts to build innovative solutions that address our company?s evolving business challenges.
Primary Responsibilities:
Lead the design and development of ML pipelines for advanced AI algorithms and ML models to solve complex problems across diverse business domains.
Collaborate on development of ML architecture and implement robust, efficient, and scalable AI systems that integrate seamlessly with existing infrastructure and platforms.
Collaborate with research scientists, data scientists, and software engineers to translate research findings into practical, scalable AI solutions.
Evaluate and experiment with emerging AI technologies, frameworks, and methodologies to stay at the forefront of innovation. Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and growth.
Collaborate with stakeholders to understand requirements, gather feedback, and iterate on AI solutions to ensure alignment with business objectives.
Deploy, test, and optimize ML models and data pipelines in production environments.
Perform model tuning, prompt tuning, and other ML optimization processes alongside other technical experts to maximize the mission impact of the AI product.
Participate in the delivery, evaluation, and maintenance of enterprise products, ensuring they meet high-quality standards.
Qualifications:
Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
5+ years of experience in a similar role in a production environment.
Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
Hands-on experience with cloud computing platforms such as AWS.
Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, IBM MQ, Apache Kafka, etc.
Experience with iterative development processes, thriving in dynamic and agile environments.
Ability to own ML delivery tasks end-to-end with little to no direct support. Hands-on experience in deploying machine learning models into production environments.
Strong understanding of software design patterns, principles, architecture, and operations.
Strong communication skills and the ability to collaborate effectively with business partners, vendors, end users, and cross-functional teams
Benefits:
York Solutions Offers a generous benefits package for eligible full-time employees:

  • BCBS Medical with 3 Plans to choose from (PPO and High deductible PPO plans with Health Savings Program)
  • Delta Dental plan with 2 free cleanings and insurance discounts
  • Eye Med Vision with annual check-ups and discounts on lens
  • Life and Accidental Death Insurance paid by company
  • John Hancock 401(k) Retirement Plan with discretionary company match
  • Voluntary Insurance programs such as: Hospital Indemnity, Identity Protection, Legal Insurance, Long Term Care, and Pet Insurance.
  • Flexible work environment with some remote working opportunities
  • Strong fun and teamwork environment
  • Learning, development, and career growth

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