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Machine Learning Engineer Quantization Jobs in Kansas

Shamrock Trading Corp.

Senior Data Scientist

Overland Park, KS · On-site

$110 - $150/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Data Scientists partner closely with business stakeholders, analysts, and Machine Learning Engineers to explore data, build and evaluate models, and communicate findings that drive efficiency, enable ...

Accenture

Senior Data Scientist

Overland Park, KS · On-site

Collaborate with data engineers, software engineers, machine learning engineers, architects, cybersecurity specialists, and platform teams to operationalize scalable AI solutions using MLOps ...

27Global

Data Engineer II

Leawood, KS · On-site

$111K - $133K/yr

Design and optimize data pipelines that support AI, machine learning, and advanced analytics workloads. * Implement data preprocessing, feature engineering, and real-time inference capabilities for ...

27Global

Data Engineer III

Leawood, KS · On-site

$111K - $133K/yr

Lead efforts to optimize data pipelines that support AI, machine learning, and advanced analytics workloads. * Implement and productionize feature engineering pipelines, model data pipelines, and ...

Amgen

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

The BioIntelligence team applies machine learning, statistical modeling, and generative AI approaches to predict critical properties of engineered biologics and enable data-driven therapeutic design.

Propio

AI Engineer II - Translation

Leawood, KS · On-site

We are seeking an AI Engineer II - Translation that will design and optimize machine learning solutions that enhance Propio's translation and localization capabilities, working closely with the ...

Propio

AI Engineer II - Translation

Overland Park, KS · On-site

We are seeking an AI Engineer II - Translation that will design and optimize machine learning solutions that enhance Propio's translation and localization capabilities, working closely with the ...

StackAdapt

$105K - $138K/yr

... machine learning, bid price optimization, user-profile enrichment, and more. The StackAdapt bidding ... Lead and collaborate with a team of engineers to design, implement, and optimize our programmatic ...

Ascend Learning

Sr Data Scientist

Leawood, KS · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design and implement statistical models, anomaly detection algorithms, and machine learning ... Partner with Psychometricians, Data Engineering, IT security, and remote proctoring vendors to ...

Garmin

Data Scientist 2

Olathe, KS · On-site

In addition, under guidance or with minimal supervision, this role will apply machine learning, statistical analysis, and data engineering techniques to address challenging business problems.

Garmin Ltd.

Data Scientist 2

Olathe, KS · On-site

$110 - $160/hr

In addition, under guidance or with minimal supervision, this role will apply machine learning, statistical analysis, and data engineering techniques to address challenging business problems.

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Machine Learning Engineer Quantization information

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 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 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 Kansas?

For Machine Learning Engineer Quantization jobs in Kansas, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in Kansas look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Kansas are:

Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Kansas as of June 2026, with employment types broken down into 76% Full Time, 23% Part Time, and 1% Temporary. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Senior Data Scientist

Shamrock Trading Corporation

Overland Park, KS • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago

Shamrock Trading Corporation rating

9.1

Company rating: 9.1 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

About Shamrock Trading Corporation
Shamrock Trading Corporation is a family of brands that has been serving the transportation and logistics industries since 1986. Shamrock offers factoring solutions, export financing, third-party logistics, a fuel card program and trucking technology.
Shamrock's mission since the start has been to create value and success for our customers, our partners and our people. Strong ethics, dedication to our customers and close attention to the marketplace are critical to the success and growth of the Shamrock brands. Shamrock is headquartered in Overland Park, Kansas, with multiple offices throughout the U.S. Overland Park is a great place to live, work and play, being conveniently located within driving distance of everything Kansas City has to offer. Housed within the heart of Overland Park, our offices include 4 gorgeous towers on the East and West sides of Metcalf Ave. With a heavy community presence and a winning culture, Shamrock is a great place to work in Overland Park!
Why You'll Love Working Here
Our award-winning culture is a testament to our commitment to growth, recognition and empowerment. From day one, we prioritize employees first, encouraging them to think and act like owners and providing endless opportunities for growth and self-development, both personally and professionally. Shamrock has been recognized as one of America's 2025 "Most Loved Workplaces" by Newsweek.
At Shamrock, we hire bright, ambitious people and give them the tools they need for a successful, long-term career here. Shamrock also offers a premier set of benefits for employees and their families:
  • Training and Development: Ongoing training and professional development opportunities
  • Medical: Fully paid healthcare, dental and vision premiums for employees and eligible dependents, and gym benefits
  • Financial: Generous company 401(k) contributions and employee stock ownership after one year
  • Work-Life Balance: Competitive PTO and fully paid time off opportunities to volunteer within your community

About the Role
Shamrock Trading Corporation is looking for a Data Scientist to join our team with a focus on fraud detection and risk assessment across our factoring, payments, lending, and freight marketplace businesses. Data Scientists partner closely with business stakeholders, analysts, and Machine Learning Engineers to explore data, build and evaluate models, and communicate findings that drive efficiency, enable risk management, and support strategic objectives.
This role will apply statistical, analytical, and machine learning techniques to help Shamrock better identify suspicious behavior, reduce financial loss, improve risk decisioning, and support faster, more confident customer funding decisions. The Data Scientist will work closely with Product, Credit, Risk, Operations, Data Services, Machine Learning Engineers, and business stakeholders to understand fraud patterns, build risk signals, evaluate models, and translate findings into practical business action.
This role is well-suited for a data scientist or advanced analytics professional with experience in fraud, risk, credit, marketplace abuse, payments, lending, logistics, or identity verification who wants to apply those skills to complex real-world problems in freight and financial services.
What You'll Do
  • Translate fraud, risk, and credit questions into analytical and modeling approaches
  • Analyze invoice, funding, payment, carrier, debtor, customer, behavioral, and operational data to identify risk patterns and emerging fraud trends
  • Develop and evaluate analytical and machine learning models to support fraud detection, risk scoring, anomaly detection, and early warning indicators
  • Partner with Product, Credit, Risk, Audit, Operations, and business stakeholders to define risk signals, success metrics, decision thresholds, and model evaluation criteria
  • Coordinate with Machine Learning team to transfer custom models into production deployments and platform integrations
  • Partner with Data Analysts and BI teams to connect fraud and risk initiatives with reporting, monitoring, and business performance metrics
  • Document assumptions, methodologies, data limitations, model performance, and findings to support transparent decision-making
  • Stay current on fraud patterns and risk approaches across factoring, freight, logistics, payments, lending, and marketplace businesses

What You'll Bring
Required
  • Bachelor's degree in a quantitative field (Statistics, Data Science, Analytics, Computer Science, Applied Mathematics, Engineering), or equivalent practical experience
  • Experience with relational databases and SQL
  • Experience using statistical programming languages (Python, R, etc.)
  • Knowledge of modern data platforms or cloud environments (Databricks, AWS, etc.)
  • Experience using Git and collaborative development workflows
  • Experience applying statistical or analytical techniques to real-world business problems (regression, classification, distributions, optimization, etc.)
  • Experience visualizing/presenting data for stakeholders (Power BI, Tableau, etc.)
  • Strong analytical thinking, problem-solving skills, and curiosity about business, fraud, and risk drivers
  • A drive to learn new technologies, fraud patterns, risk techniques, and industry context

Preferred
  • Experience in fraud analytics, risk analytics, credit risk, underwriting, payments fraud, marketplace fraud, identity verification, logistics, freight brokerage, factoring, asset-based lending, SMB lending, commercial lending, or financial services
  • Experience building or supporting fraud detection, anomaly detection, risk scoring, credit scoring, identity risk, or transaction monitoring models
  • Experience working with adversarial risk problems where bad actors change behavior in response to controls
  • Experience with entity resolution, graph analytics, network analysis, behavioral analytics, or relationship-based risk detection
  • Experience working with invoice, payment, bank account, carrier, debtor, customer, document, device, or transaction-level data
  • Experience partnering with Product, Engineering, Operations, Credit, Risk, or Compliance teams to move analytical work into business processes or production systems

Apply Today!
We're so excited to connect with you! If you want to work with forward-thinking people in an award-winning culture, submit your application today.
#LI-MB1 #LI-Onsite
Having trouble submitting your application? Contact us at Recruiting@shamrocktradingcorp.com for support.

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