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Machine Learning Engineer Quantization Jobs in Washington

UNISSANT

Machine Learning Engineer

Ashburn, VA · On-site

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands-on experience in machine learning, advanced analytics, and AI ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

Job Summary : aisquared is a company focused on AI solutions, and they are seeking a highly skilled Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ...

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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.

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Cities in Washington with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

Ashburn, VA • On-site

UNISSANT
See more jobs at UNISSANTexternal

Full-time

Re-posted 6 days ago

Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com.

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands-on experience in machine learning, advanced analytics, and AI-driven product development, with the ability to turn complex data into practical, mission-focused solutions. This role is well suited for a technically strong professional who enjoys building and improving models, partnering across Agile teams, and supporting the delivery of innovative capabilities from early concept through deployment and ongoing performance optimization.

Essential Duties and Responsibilities:

  • Design, develop, and maintain machine learning models that support a variety of AI applications.
  • Analyze large and complex datasets to identify trends, test hypotheses, and generate actionable insights using statistical and analytical methods.
  • Build and support reliable data pipelines that improve data quality, accessibility, and usability for machine learning and analytics initiatives.
  • Collaborate with data engineering and cross-functional teams to enhance data workflows and optimize supporting infrastructure.
  • Contribute to AI product development activities across the lifecycle, including prototyping, implementation, deployment, and post-production support.
  • Monitor model effectiveness and product performance metrics, and perform ongoing enhancements to improve accuracy, scalability, and reliability.
  • Work closely with product managers, developers, designers, and QA teams within a large Agile development environment.

Work Experience and Job Skills:

  • Three (3) to four (4) years of hands-on experience in machine learning engineering, AI solution development, data analytics, or related technical work is preferred.
  • Experience supporting AI, machine learning, or advanced analytics initiatives is required.
  • Demonstrated experience developing and deploying AI/ML models in a production environment.
  • Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development.
  • Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with MLOps practices, CI/CD pipelines, and model deployment processes.
  • Working knowledge of SQL and NoSQL databases and data processing tools such as Apache Spark or Hadoop.
  • Experience with analytics and visualization tools such as Tableau, Power BI, matplotlib, or Plotly.
  • Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related services is preferred.
  • Strong problem-solving abilities, attention to detail, and organizational skills.
  • Ability to manage multiple assignments independently while collaborating effectively across technical and business teams.
  • Experience working in Agile product development environments is a plus.

Education:

  • Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related technical field is required.
  • Master's Degree in a relevant field is preferred.
  • Equivalent combination of education and experience may be considered in lieu of strict degree requirements, based on client standards.

Certificates, Licenses and Registrations:

  • Relevant certifications in cloud computing, machine learning, data science, or data engineering are a plus.
  • Additional technical certifications may be considered based on program requirements.

Communication Skills:

  • Excellent verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Strong interpersonal skills and the ability to collaborate effectively across cross-functional teams in a client-facing environment.

Clearance Requirements:

  • Ability to obtain and maintain a Public Trust position and favorable suitability determination based on a CBP background investigation is required.

Travel:

  • This is a hybrid position based in Ashburn, VA, with onsite support expected one to two days per week and additional onsite presence as required by mission needs.

Environmental Requirements:

  • Mainly a routine office environment.
  • May be required to lift up to ten (10) pounds.
  • Flexible in working extended hours.

The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions of this position.

Please note: Candidate(s) will be required to go through pre-employment screening.

Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets)

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