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Machine Learning Engineer Quantization Jobs in Plano, TX

Bespoke Labs

Machine Learning Engineer

Dallas, TX

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Mckinney, TX

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Mckinney, TX · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Dallas, TX · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Vanguard

Manager, Machine Learning Engineer

Dallas, TX

$101K - $133K/yr

Leads a team of Machine Learning Engineers responsible for designing, building, deploying, and scaling AI/ML solutions that support Financial Advisory Services (FAS) business objectives. Partners ...

T-Mobile

Sr Engineers, Machine Learning

Frisco, TX · On-site

$97K - $134K/yr

... all. Sr Engineers, Machine Learning located in Frisco, Texas will enable systems for coding ... quantization, distillation, or runtime optimization), observability instrumentation, and CI/CD ...

Crowe LLP

Machine Learning Engineer

Plano, TX

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Crowe LLP

Machine Learning Engineer

Dallas, TX

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Citi

Machine Learning Engineer Vice President

Irving, TX · On-site

$142K - $213K/yr

We are seeking a highly skilled and motivated Machine Learning Engineer to join our technology team. The ideal candidate will be responsible for designing, developing, and deploying cutting-edge ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Plano, TX

Machine Learning Engineer Quantization information

See Plano, TX salary details

$30.1K

$123.2K

$185.2K

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

As of Sep 14, 2026, the average yearly pay for machine learning engineer quantization in Plano, TX is $123,243.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,100.00 and $148,300.00 per year, depending on experience, location, and employer.

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 Plano, TX?

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

What job categories do people searching Machine Learning Engineer Quantization jobs in Plano, TX look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Plano, TX are:

Machine Learning Engineer Quantization jobs near you

Junior Machine Learning Engineer

Plano, TX • On-site

MyFunded Futures
See more jobs at MyFunded Futuresexternal

Full-time

Posted 13 days ago

Key responsibilities

  • Develop, test, validate, and maintain machine learning models.

  • Build and maintain data pipelines and analytical datasets on the company's cloud data platform.

  • Evaluate model performance and document assumptions, methods, and limitations.

Job description

At My Funded Futures, we're transforming the world of proprietary trading by giving traders the capital, tools, and community they need to succeed.
We blend innovation, transparency, and performance to create opportunity - helping traders scale faster and smarter. If you're passionate about fintech, financial markets, and data-driven growth, you'll fit right in.
Explore our open roles below and see how you can help us shape the future of funded trading.
The Junior ML Engineer will support the Company's data science function by developing, validating, and maintaining machine learning models and the data pipelines behind them. This is a hands-on, applied role: you will work with real data on problems that directly shape the product and the business, and you will be expected to explain what your models do and why they can be trusted.
You will partner closely with the Data Science and Analytics team and with stakeholders across the organization, translating business questions into well-defined analytical problems and presenting results in terms decision-makers can act on.
This role is ideal for someone early in their career who has already built and shipped machine learning models and who wants broader exposure across modeling, analytics, and data engineering.
Key Responsibilities
  • Develop, test, validate, and maintain machine learning models under the guidance of senior team members.
  • Build and maintain data pipelines and analytical datasets on the Company's cloud data platform.
  • Evaluate model performance rigorously and document assumptions, methods, and limitations.
  • Support statistical analysis, forecasting, and experimentation to inform business decisions.
  • Present technical findings clearly to non-technical audiences.
  • Contribute to standards for model documentation, validation, and monitoring.
Qualifications
  • Bachelor's degree (or equivalent) in computer science, mathematics, engineering, or a related field, with coursework in machine learning or statistical learning. Graduate degree is a plus.
  • Strong Python and PySpark skills, with the ability to write clean, tested, maintainable code.
  • Hands-on experience with a cloud data platform (Databricks, Snowflake, Fabric, or similar)
  • Strong SQL, including window functions and multi-table joins.
  • Solid understanding of core ML concepts: cross-validation, overfitting, class imbalance, data leakage (including in time-ordered data), and choosing evaluation metrics appropriate to the problem.
  • Hands-on experience with:
    • Gradient-boosted trees (XGBoost, LightGBM)
    • Logistic regression, support vector machines, k-nearest neighbors
    • Clustering methods (k-means and others)
  • Experience with some of the following: survival / time-to-event analysis, experiment design and causal inference, simulation and Monte Carlo methods, probability calibration, Bayesian or hierarchical modeling, model monitoring and drift detection
  • Experience taking a model from development into a scheduled or production environment
  • Docker, CI/CD, and workflow orchestration experience
  • Ability to explain model behavior, including feature importance, calibration, and limitations.
  • Ability to gather and present technical results to a non-technical audience.
  • Proven experience as a machine learning engineer or in a similar role is a plus.
  • Fintech, trading, or financial services background is a plus.

EEO Statement
Equal Employment Opportunity
My Funded Futures is an equal opportunity employer. We believe that diversity drives innovation and success. We are committed to building an inclusive environment where every team member feels valued, respected, and supported-regardless of race, color, religion, gender, gender identity, sexual orientation, national origin, age, disability, veteran status, or any other protected characteristic.
Pay Transparency
In compliance with pay transparency laws, My Funded Futures provides compensation ranges in job postings where required. Final compensation may vary based on experience, qualifications, and location. We also offer comprehensive benefits and performance-based incentives.
Accessibility / Accommodation Statement
If you require assistance or an accommodation during the application process, please contact our HR team at careers@myfundedfutures.com.
Work Authorization
Applicants must be authorized to work in the applicable country without employer sponsorship. The Company does not offer visa sponsorship or immigration assistance for this position.

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