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Machine Learning Engineer Quantization Jobs in New York

ClifyX

Machine Learning Engineer

Manhattan, NY · On-site

Machine Learning Engineer The Viacom Data Platform is looking for an awesome Machine Learning Engineer with hands-on experience in developing and maintaining scalable machine learning applications ...

Point72

Machine Learning Engineer

New York, NY · On-site

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team. This role will apply the latest AI technologies to solve various real-world problems and streamline day ...

Spotify

Machine Learning Engineer

New York, NY · On-site +1

$170K - $212K/yr

We're looking for a Machine Learning Engineer to help us build systems that more accurately understand the performance that promotion can have, giving customers actionable insights for building their ...

Spotify

Machine Learning Engineer

New York, NY · On-site +1

$170K - $212K/yr

We're looking for a Machine Learning Engineer to help us build systems that more accurately understand the performance that promotion can have, giving customers actionable insights for building their ...

Point72

Machine Learning Engineer

New York, NY · On-site

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team. This role will apply the latest AI technologies to solve various real-world problems and streamline day ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · Hybrid

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · Hybrid

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Preferred Qualifications * Experience with model quantization and optimization for mobile ...

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

Machine Learning Engineer

Focus Financial Partners

Manhattan, NY • On-site

Full-time

Posted 16 days ago

Job description

Job Summary:
Focus Financial Partners is a leading financial services firm that blends deep expertise with a client-first fiduciary philosophy. They are seeking a skilled Machine Learning Engineer to design, deploy, and maintain production-grade machine learning systems, collaborating with cross-functional teams to create scalable applications.
Responsibilities:
• Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications.
• Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments.
• Design and implement data pipelines and workflows that support training, inference, and model lifecycle management.
• Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows.
• Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles.
• Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices.
• Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices.
• Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities.
Qualifications:
Required:
• Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles.
• Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask).
• Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with CI/CD pipelines, testing automation, and version control using Git.
• Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts.
• Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams.
Preferred:
• Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML).
Company:
Focus Financial Partners is a partnership of fiduciary wealth management firms that offers support and access to capital for growth. Founded in 2006, the company is headquartered in New York, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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