ZipRecruiter

Log In

1

Machine Learning Engineer Quantization Jobs in Colorado Springs, CO

GXM Consulting

DevSecOps Engineer

Colorado Springs, CO · On-site

$90K - $165K/yr

GXM is seeking a DevSecOps Engineer to join our team to support advanced defense and space-related ... Experience deploying AI/ML models, data pipelines, or machine learning platforms into operational ...

GRVTY

Data Scientist 3

Colorado Springs, CO · On-site

$155K - $185K/yr

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python ...

GRVTY

Data Scientist 3

Colorado Springs, CO

$155K - $185K/yr

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python ...

Auria

Chief Engineer

Colorado Springs, CO · On-site +1

$160K - $190K/yr

... machine learning (ML); and Cybersecurity and zero-trust architecture. WHAT YOU CAN EXPECT TO DO ... Bachelor's degree in engineering, computer science, or related field. * 10+ years' experience of ...

Auria

Chief Engineer

Colorado Springs, CO · On-site +1

$169K - $190K/yr

... machine learning (ML); and Cybersecurity and zero-trust architecture. WHAT YOU CAN EXPECT TO DO ... Bachelor's degree in engineering, computer science, or related field. * 10+ years' experience of ...

Auria

Chief Engineer

Colorado Springs, CO · On-site +1

$169K - $190K/yr

... machine learning (ML); and Cybersecurity and zero-trust architecture. WHAT YOU CAN EXPECT TO DO ... Bachelor's degree in engineering, computer science, or related field. * 10+ years' experience of ...

Booz Allen Hamilton

Cribl Engineer

Colorado Springs, CO

$99K - $225K/yr

Cribl Engineer The Opportunity: Are you excited at the prospect of developing innovative solutions ... Experience with big data analytics, machine learning, artificial intelligence, or anomaly detection

previous page

Showing results 41-60

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Colorado Springs, CO

Machine Learning Engineer Quantization information

See Colorado Springs, CO salary details

$31K

$126.9K

$190.7K

How much do machine learning engineer quantization jobs pay per year?

As of Aug 7, 2026, the average yearly pay for machine learning engineer quantization in Colorado Springs, CO is $126,901.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $152,800.00 per year, depending on experience, location, and employer.

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 Colorado Springs, CO? For Machine Learning Engineer Quantization jobs in Colorado Springs, CO, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Colorado Springs, CO look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Colorado Springs, CO are:
What cities near Colorado Springs, CO are hiring for Machine Learning Engineer Quantization jobs? Cities near Colorado Springs, CO with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Colorado Springs, CO as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $126,901 per year, or $61 per hour.

AI/ML Engineer

Frontier Technology Inc.

Colorado Springs, CO • Remote

$190K - $220K/yr

Full-time

Re-posted 14 days ago

Job description

Overview

FTI Defense is seeking a hands-on AI/ML Engineer to design, build, and deploy advanced machine learning solutions supporting defense and national security missions. This role focuses on execution in oversight, ideal for an engineer who thrives in the code, enjoys building end-to-end pipelines, and takes pride in seeing their work directly impact operational systems.

FTI Defense delivers mission-focused solutions to the Department of Defense/Depratment of War (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

Responsibilities
  • Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
  • Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
  • Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference orchestration).
  • Implement and optimize vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval architectures (RAG, graph, hybrid).
  • Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
  • Experiment with fine-tuning and optimization of LLMs and task-specific models (LoRA, QLoRA, PEFT).
  • Contribute to agent-based applications using frameworks like LangGraph, AutoGen, CrewAI, or DSPy.
  • Integrate AI services into real-world systems via APIs, event-driven workflows, or UI copilots.
  • Collaborate with data engineers, software developers, and mission analysts to ensure AI models are production-ready and aligned with customer needs.
  • Participate in peer reviews, contribute to shared repositories, and document models and experiments for reproducibility.
Education/Qualifications

Minimum Requirements:

  • Must be a U.S. citizen and be willing to obtain and maintain a security clearance, as needed.
  • 6-10+ years of professional experience developing and deploying AI/ML solutions in production environments.
  • Minimum of 3 years' professional experience within the Department of Defense/Department of War (DoD/DoW) AI assurance, security, and deployment environments.
  • Strong Python development skills with hands-on experience building AI/ML solutions.
  • Direct experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, or LangChain.
  • Proven ability to build and deploy MLOps pipelines using MLflow, Kubeflow, DVC, or equivalent.
  • Working knowledge of vector databases (Milvus, Pinecone, Chroma, FAISS) and retrieval-based architectures (RAG, hybrid, graph).
  • Professional experience fine-tuning and evaluating LLMs or smaller task-specific models using LoRA, QLoRA, or PEFT.
  • Professional experience integrating AI capabilities into production systems or mission applications.

 Preferred Qualifications:

  • Familiarity with agentic frameworks (LangGraph, AutoGen, CrewAI, DSPy) and multi-agent reasoning.
  • Understanding of prompt engineering, retrieval quality, and grounding methods.
  • Exposure to GPU-based or edge inference environments.
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related technical field.
  • Active Secret clearance preferred; ability to obtain one is required.

For this role, the compensation range for candidates is $190k-$220k . *Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience. FTI has a location-based compensation structure; there may be a different range for candidates in other locations.

#LI-KM1

#LI-Remote

Employment Type: FULL_TIME

Apply