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Machine Learning Engineer Quantization Jobs in Florida

They are seeking a Machine Learning Engineer to own the design and implementation of core pricing services, collaborating with cross-functional teams to enhance their pricing platform and drive ...

Junior Machine Learning Engineer

Melbourne, FL ยท On-site

$65K - $106K/yr

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

As a software engineer on the team, you'll collaborate with data scientists, machine learning engineers, product managers, and partner engineering and operations teams to turn ideas into resilient ...

Job Title Mandatory skills - A blend of person who is familiar with Machine Learning Models, Docker ... Work on feature engineering to ensure most information going into the model for prediction accuracy ...

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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 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- Services

Machine Learning Engineer- Services

Opendoor

Miami, FL โ€ข On-site

Full-time

Posted 7 days ago


Job description

Job Summary:
Opendoor is dedicated to transforming the homeownership experience, helping individuals buy and sell homes with ease. They are seeking a Machine Learning Engineer to own the design and implementation of core pricing services, collaborating with cross-functional teams to enhance their pricing platform and drive improvements in reliability and scalability.
Responsibilities:
โ€ข Own the design, implementation, and evolution of core pricing services
โ€ข Design data models and write high-performance SQL over large PostgreSQL datasets
โ€ข Architect and improve APIs and integrations with Opendoorโ€™s core marketplace platform
โ€ข Lead technical design reviews and set best practices for code quality, testing, and observability
โ€ข Partner with data science to productionize pricing models and build robust model-serving pipelines
โ€ข Drive reliability, latency, and scalability improvements across pricing systems
โ€ข Mentor other engineers and help grow the technical capabilities of the team
โ€ข Collaborate with product and cross-functional partners to define and deliver roadmap projects end to end
Qualifications:
Required:
โ€ข 5+ years of professional backend software engineering experience
โ€ข Significant experience building and operating production systems in Go or Python
โ€ข Deep proficiency with SQL and relational databases (PostgreSQL preferred)
โ€ข Strong track record designing, building, and evolving APIs in a microservices environment
โ€ข Experience with distributed systems concepts (scalability, consistency, resiliency, monitoring)
โ€ข Experience leading technical projects from design through rollout and support
โ€ข Ability to communicate complex technical decisions clearly to both technical and non-technical stakeholders
Preferred:
โ€ข Experience with Kafka or similar event-streaming technologies
โ€ข Experience using AI-assisted development tools (e.g. Claude Code, Cursor AI, Github Copilot)
โ€ข Experience with BPMN or other workflow engines and long-running business processes
โ€ข Experience with Redis or other caching / storage optimization technologies
โ€ข Experience with gRPC and service-to-service communication patterns at scale
โ€ข Prior experience in pricing, marketplaces, or other data-intensive domains
Company:
Founded in 2014, Opendoorโ€™s mission is to power lifeโ€™s progress one move at a time. Founded in 2014, the company is headquartered in Tempe, USA, with a team of 1001-5000 employees. The company is currently Late Stage.