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Machine Learning Engineer Quantization Jobs in Kansas

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.

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 ...

Lawton OK; or Round Rock, TX Job Purpose/Summary Work with our team of engineers, scientists and human factors professionals to develop machine learning and other algorithm data capabilities for ...

CNC Machine Operator

Olathe, KS · On-site

$20 - $28/hr

As a CNC Machine Operator , you'll work with advanced technologies such as AI, Machine Learning ... You'll contribute to state-of-the-art projects that push the boundaries of engineering and ...

AI Engineer

Leawood, KS · On-site

$111K - $133K/yr

Bachelor's degree in Computer Science, Machine Learning, Data Science, Computational Linguistics, Linguistics, Statistics, or a related field, or equivalent practical experience. * 4+ years of ...

As a CNC Machine Operator , you'll work with advanced technologies such as AI, Machine Learning ... You'll contribute to state-of-the-art projects that push the boundaries of engineering and ...

Hands-on experience building and validating machine learning models on tabular and time-series data, including feature engineering, cross-validation, and methods such as regression, tree-based models ...

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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 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:
Senior Director - BioIntelligence

Senior Director - BioIntelligence

Amgen

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 13 hours ago


Job description

Career CategoryScientificJob DescriptionJoin Amgen's Mission of Serving Patients

At Amgen, if you feel like you're part of something bigger, it's because you are. Our shared mission-to serve patients living with serious illnesses-drives all that we do.

Since 1980, we've helped pioneer the world of biotech in our fight against the world's toughest diseases. With our focus on four therapeutic areas -Oncology, Inflammation, General Medicine, and Rare Disease- we reach millions of patients each year. As a member of the Amgen team, you'll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you'll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Senior Director - BioIntelligenceWhat you will do

Let's do this. Let's change the world. The AI & Data for Engineered Biologics (AIDE) organization at Amgen is seeking a Senior Director to lead our BioIntelligence team. The Senior Director will lead the development and deployment of AI-driven predictive modeling capabilities for biologics discovery in our Large Molecule Discovery organization.

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. These capabilities support programs across discovery, protein engineering, immunology, and developability by transforming experimental data into actionable predictive models and scientific software.

In this vital role, you will lead a sophisticated multidisciplinary team of machine learning and data scientists responsible for developing scalable AI solutions that accelerate biologics discovery. You will define the scientific and technical strategy for AI-driven biologics property prediction while partnering closely with experimental teams, data engineering groups, and software platform teams across Amgen.

This role requires a leader with deep expertise in machine learning for biological systems, experience building and mentoring high-performing scientific teams, and a track record of translating advanced computational methods into impactful research capabilities.

Key Responsibilities:

Strategic Leadership

  • Lead the BioIntelligence Team within our Large Molecule Discovery organization, defining strategy and priorities for AI-driven biologics modeling.
  • Develop and execute a roadmap for machine learning and AI approaches that accelerate engineered biologics discovery.
  • Align BioIntelligence capabilities with broader Research and Large Molecule Discovery priorities.

AI for Biologics Modeling

  • Oversee development of predictive models for key biologics properties, including developability, stability, manufacturability, and immunogenicity.
  • Advance modeling approaches using modern AI techniques such as:
    • protein language models
    • generative modeling and inverse folding
    • representation learning
    • active learning and Bayesian optimization
  • Guide the use of multimodal biological datasets including sequence, structure, and experimental assay data.

Platform Integration & Model Deployment

  • Lead development of production-quality research software and deployable ML models used across discovery teams.
  • Partner with software engineering and data platform teams to ensure models are scalable, reproducible, and integrated into R&D workflows.
  • Establish best practices for MLOps, model lifecycle management, and reproducible scientific computing.

Cross-Functional Collaboration

  • Work closely with teams across protein engineering, immunology, display technologies, systems biology, and discovery platforms.
  • Partner with experimental scientists to design data generation strategies and active learning loops that improve model performance.
  • Collaborate with data engineering and informatics groups to improve data accessibility, quality, and reuse across the discovery ecosystem.

Team Leadership

  • Build, mentor, and lead a high-performing team of machine learning scientists and computational biologists.
  • Foster a culture of scientific rigor, innovation, and collaboration between computational and experimental scientists.
  • Drive adoption of AI solutions across research teams by ensuring models are interpretable, robust, and scientifically trusted.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The dynamic professional we seek is a leader with these qualifications.

Basic Qualifications:

Doctorate degree in Computational Biology, Machine Learning, Bioinformatics, Computer Science, Biophysics, or related field and 5 years of experience applying machine learning or computational modeling to biological systems.

OR

Master's degree in Computational Biology, Machine Learning, Bioinformatics, Computer Science, Biophysics, or related field and 9 years of experience applying machine learning or computational modeling to biological systems.

OR

Bachelor's degree in Computational Biology, Machine Learning, Bioinformatics, Computer Science, Biophysics, or related field and 11 years of experience applying machine learning or computational modeling to biological systems.

In addition to meeting at least one of the above requirements, you must have at least 5 years experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation or resources. Your managerial experience may run concurrently with the required technical experience referenced above

Preferred Qualifications:

  • Experience developing machine learning models for biologics properties
  • Experience with protein language models, diffusion models, generative modeling, or structure-based design
  • Experience deploying ML models into production scientific software platforms
  • Expertise in protein sequence or structure modeling, antibody engineering, or computational immunology
  • Strong leadership experience managing multidisciplinary computational science teams
  • Track record of publications, patents, or deployed technologies in AI for life sciences
What you can expect of us

As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way.

The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.

In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:

  • A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
  • A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
  • Stock-based long-term incentives
  • Award-winning time-off plans
  • Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.
Apply now and make a lasting impact with the Amgen team.careers.amgen.com

In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

Application deadline

Amgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.

Sponsorship

Sponsorship for this role is not guaranteed.

As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.

Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Amgen will consider for employment qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance.

Salary Range

239,775.00 USD - 295,217.00 USD