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Machine Learning Engineer Quantization Jobs in Florida

Intraedge

Machine Learning Engineer

Sunrise, FL · Hybrid

Machine Learning Engineer - Generative Al Long term contract Sunrise, FL (Hybrid-3 days onsite) Direct client- Immediate client interview We are seeking a Machine Learning Engineer to design, build ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and ...

Citadel

Machine Learning Engineer

Miami, FL · On-site

Skills and Preferred Qualifications * 2+ years of experience in machine learning and software development. * Strong engineering skills, including Python, CUDA, C++. * Experience building distributed ...

Indeed

Machine Learning Engineer

Miami, FL

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

ClifyX

Sr. Machine Learning Engineer

Bradenton, FL · Remote

$111K - $146K/yr

Sr. Machine Learning Engineer The Sr. Machine Learning Engineer collaborates with the team of Data Scientists and Data Analysts in creating scalable, data-driven, customer-centric solutions, capable ...

ENSCO

Machine Learning Engineer

Melbourne, FL

$72K - $131K/yr

Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

$73K - $131K/yr

Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks ...

SynergisticIT

Machine Learning Engineer

Orlando, FL

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/ Data Scientists, Machine Learning engineers for full time positions ...

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

Machine Learning Engineer

Intraedge

Sunrise, FL • Hybrid

Other

Posted 19 days ago

Job description

Machine Learning Engineer - Generative Al

Long term contract

Sunrise, FL (Hybrid-3 days onsite)

Direct client- Immediate client interview

Job description:

We are seeking a Machine Learning Engineer to design, build, and deploy Generative Al solutions powered by Large Language Models (LLMs). In this role, you will work on end-to-end GenAl use cases, from model selection to production-ready systems.

Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google Cloud Platform

Key Responsibilities

Develop and productionize GenAl applications using LLMs (open-source and closed-source).

Design agentic workflows using LangChain and LangGraph.

Implement short-term and long-term memory strategies for LLM-based systems.

Optimize prompts, retrieval pipelines, and orchestration logic.

Colaborate with product and platform teams to deliver scalable Al solutions.

Required Qualifications

Strong experience with LLMs (e.g., OpenAl, Anthropic, Llama, Mistral).

Hands-on experience with LangChain and/ or LangGraph.

Solid understanding of LLM memory architectures and state management.

Proficiency in Python and ML engineering best practices.

Nice to Have

Experience with Google Cloud Platform services (e.g.,Vertex Al, BigQuery, GCS).

Experience deploying ML/GenAl systems in production environments.

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About IntraEdge

Sourced by ZipRecruiter

At heart, we are a technology, products and services organization In our soul, it’s the people who make us what we are — the professionals we train and connect to next-level opportunities and the experts who create innovative solutions and value for our national and international partners. It’s true that innovative technology can provide a major boost to your business, but you also need the right talent pushing it forward. This critical combination is what we offer all of our partners: cutting edge tech solutions and the expertise to bring it to life.

Industry

It services

Company size

1,001 - 5,000 Employees

Headquarters location

Chandler, AZ, US

Year founded

2002

Social media

Instagram

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