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Machine Learning Engineer Quantization Jobs in Houston, TX

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Senior/Principal Machine Learning Engineer 200-300k Remote position possible Description * Develop solutions for autonomous driving, from experimentation to full commercialization. * Explore new ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Senior AI Engineer

Houston, TX · On-site

$99K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

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Machine Learning Engineer Quantization information

See Houston, TX salary details

$30.1K

$123K

$184.8K

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

As of Jun 20, 2026, the average yearly pay for machine learning engineer quantization in Houston, TX is $122,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,900.00 and $148,000.00 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 job categories do people searching Machine Learning Engineer Quantization jobs in Houston, TX look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Houston, TX are:
What cities near Houston, TX are hiring for Machine Learning Engineer Quantization jobs? Cities near Houston, TX with the most Machine Learning Engineer Quantization job openings:
Principal Machine Learning Engineer

Principal Machine Learning Engineer

CISCO, Inc.

Houston, TX

$291K - $369K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago


Cisco Systems rating

8.0

Company rating: 8.0 out of 10

Based on 40 frontline employees who took The Breakroom Quiz

47th of 139 rated electronics manufacturers


Job description

The application window is expected to close on:

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received .

Meet the Team

Splunk, a Cisco company, is building a safer, more resilient digital world with an end‑to‑end, full‑stack platform designed for hybrid, multi‑cloud environments. Join the AI Models team at Splunk, where we advance the state of AI for high‑volume, real‑time, multi‑modal machine‑generated data — including logs, time series, traces, and events. We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco’s global engineering capabilities. Our work spans networking, security, observability, and customer experience — designing and deploying foundation models that enhance reliability, strengthen security, prevent downtime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You’ll be part of a culture that values technical excellence, impact‑driven innovation, and cross‑functional collaboration — all within a flexible, growth‑oriented environment.

Your Impact

  • Set and Drive Vision:Define and champion the strategic vision for AI and foundation models across Splunk and Cisco platforms, shaping the research and technology roadmap to anticipate and address industry‑defining challenges.

  • Architect and Lead Breakthroughs: Lead the end‑to‑end lifecycle of research, design, and deployment for large‑scale foundation models targeting machine‑generated data, with deep focus on logs and complementary modalities (time series, traces, events).

  • Influence at Scale: Partner with executive leadership, engineering, product, and data science teams to ensure AI solutions align with broader organizational objectives, product strategies, and customer needs.

  • Mentorship and Thought Leadership: Cultivate organizational excellence by mentoring senior technical talent, fostering research communities, and driving best practices in AI across global teams.

  • Foster Innovation: Embed cutting‑edge research and technological advances into products, driving sustained competitive advantage and transformation at enterprise scale.

Minimum Qualifications:

  • PhD in Computer Science, or related quantitative field, plus7+ years of industry research experience.

  • Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learning‑based time series modeling, advanced anomaly detection, and multi-modality modeling.

  • Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)

  • Experience translating research ideas into production systems.

Preferred Qualifications:

  • Deep NLP & Domain‑Adapted LLMs: Background in building and adapting large‑scale language models (e.g., T5, BERT, LLaMA, GPTs) for specialized domains including structured/unstructured logs, text, and event sequences.

  • Log Analytics Expertise – In‑depth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.

  • Advanced Anomaly Detection – Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for high‑volume, real‑time logs data.

  • Multi‑Modal AI Modeling – Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.

  • Large‑Scale Training & Optimization – Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.

  • MLOps & Continuous Learning – Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.

  • Strong Research Track Record – Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to state‑of‑the‑art methods and real‑world applications.

Why Cisco?

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:

The starting salary range posted for this position is $291,500.00 to $369,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco’s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco’s policies:

  • 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees

  • 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco

  • Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees

  • Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)

  • 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next

  • Additional paid time away may be requested to deal with critical or emergency issues for family members

  • Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco’s policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

  • .75% of incentive target for each 1% of revenue attainment up to 50% of quota;

  • 1.5% of incentive target for each 1% of attainment between 50% and 75%;

  • 1% of incentive target for each 1% of attainment between 75% and 100%; and

  • Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

$291,500.00 - $424,400.00

Non-Metro New York state & Washington state:

$259,400.00 - $377,600.00

  • For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.

Cisco is an Affirmative Action and Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, national origin, genetic information, age, disability, veteran status, or any other legally protected basis.

Cisco will consider for employment, on a case by case basis, qualified applicants with arrest and conviction records.


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About Cisco Systems

Sourced by ZipRecruiter

Cisco Systems, a global tech titan based in San Jose, CA, US, operates in the information technology and services industry. Founded in 1984, the company was derived from a project between two computer scientists from Stanford University. They aimed to connect different networks of computer systems at the university, resulting in the first multi-protocol router, and subsequently, the birth of Cisco. As an industry-leading manufacturer of networking hardware and telecommunications equipment, Cisco's product and services range includes routers, switches, firewall devices, and telecommunication technology. The company's mission, "to shape the future of the Internet by creating unprecedented value and opportunity for our customers, employees, investors, and ecosystem partners," is a testament to its pursuit of technology-forward innovation and customer satisfaction.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1984

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