1

Modeling Engineer Jobs (NOW HIRING)

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model ...

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model ...

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model ...

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model ...

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model ...

The impact you'll make As a Modeling Engineer 3 in the WETS Product Group, your work will directly influence the design and advancement of our semiconductor capital equipment products for the ...

EMS Modeling Engineer

Matthews, NC · On-site

$87K - $120K/yr

Overview Will consider candidates near other TRC offices ( The EMS Modeling Engineer will be an essential part of our team to grow the consulting practice in the Operational Technology and Real-Time ...

EMS Modeling Engineer

Gahanna, OH · On-site

$76K - $120K/yr

Overview Will consider candidates near other TRC offices ( The EMS Modeling Engineer will be an essential part of our team to grow the consulting practice in the Operational Technology and Real-Time ...

SoC Modeling Engineer

San Diego, CA · On-site

$115K - $173K/yr

Job Area Engineering Group, Engineering Group > ASICS Engineering General Summary This role is to support expanding SoC Architecture team with modeling of various physical and performance aspects of ...

EMS Modeling Engineer

Tampa, FL · On-site

$87K - $120K/yr

Overview Will consider candidates near other TRC offices ( The EMS Modeling Engineer will be an essential part of our team to grow the consulting practice in the Operational Technology and Real-Time ...

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona's voice and multimodal agents. You will own problems across model ...

Showing results 21-40

Modeling Engineer information

See salary details

$36.5K

$111.5K

$196K

How much do modeling engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for modeling engineer in the United States is $111,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,000.00 and $132,500.00 per year, depending on experience, location, and employer.

What is a modeling engineer?

Modeling Engineers are professionals who develop mathematical or computational models to simulate real-world systems, processes, or products. They often work in fields like engineering, manufacturing, software development, or research, using advanced software tools and programming languages. Their models help predict performance, identify improvements, and optimize designs before actual implementation. Modeling Engineers collaborate closely with other engineers, designers, and stakeholders to ensure that the models meet project goals and real-world constraints.

What are the key skills and qualifications needed to thrive as a modeling engineer, and why are they important?

To thrive as a Modeling Engineer, you need a solid background in mathematics, physics, and computational modeling, often backed by a degree in engineering or a related field. Proficiency in simulation software such as MATLAB, Simulink, ANSYS, or Python-based modeling tools is typically required, along with familiarity with CAD systems. Strong problem-solving abilities, communication skills, and attention to detail help set exceptional modeling engineers apart. These skills ensure accurate model development, effective teamwork, and the ability to translate complex data into actionable engineering solutions.

How does a modeling engineer typically collaborate with other teams during a project?

Modeling Engineers frequently work in cross-functional teams, collaborating closely with design, simulation, and product development groups to ensure that models accurately reflect real-world conditions and requirements. They often participate in regular meetings to discuss project goals, share progress updates, and troubleshoot any issues that arise in the modeling process. Open communication and the ability to translate complex technical data for non-technical stakeholders are essential, as Modeling Engineers serve as a bridge between theoretical models and practical implementation. This collaborative environment helps ensure that projects are delivered efficiently and meet the necessary specifications.

What is the difference between Modeling Engineer vs Simulation Engineer?

AspectModeling EngineerSimulation Engineer
CredentialsBachelor's or Master's in Engineering, Computer Science, or related fieldsBachelor's or Master's in Engineering, Computer Science, or related fields
Work EnvironmentDesigning and developing models, working in R&D or product development teamsRunning simulations, analyzing results, often in testing or validation labs
Industry UsageAutomotive, aerospace, electronics, and manufacturing sectorsAutomotive, aerospace, electronics, and manufacturing sectors
Common Search/ComparisonModeling Engineer vs Simulation Engineer

Modeling Engineers focus on creating mathematical and computational models to represent systems or components, while Simulation Engineers run simulations based on those models to analyze performance and behavior. Both roles often overlap but serve different stages in product development and testing processes.

What does a modeling engineer do?

A modeling engineer develops and implements mathematical models to simulate physical systems, processes, or products. They use software tools like MATLAB or Simulink and often work closely with design, testing, and validation teams to optimize performance and ensure accuracy. Strong analytical skills and knowledge of engineering principles are essential for this role.
More about Modeling Engineer jobs

What states have the most Modeling Engineer jobs?

States with the most job openings for Modeling Engineer jobs include:

What are popular job titles related to Modeling Engineer jobs?

For Modeling Engineer jobs, the most frequently searched job titles are:

Infographic showing various Modeling Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 89% Full Time, 7% Part Time, and 3% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $111,510 per year, or $53.6 per hour.

AI Modeling Engineer

Los Altos, CA • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 3 days ago


Job description

Palona’s AI agents operate in real restaurant environments: noisy phone lines, varied accents, complex menus, interruptions, incomplete information, strict business rules, and customers who expect an immediate, natural response. Improving these systems requires more than selecting the newest model. It requires disciplined evaluation, high-quality data, modeling judgment, experimentation, and production feedback loops.

We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona’s voice and multimodal agents. You will own problems across model selection and routing, prompting and context, fine-tuning or post-training when justified, speech and language quality, evaluation methodology, dataset development, and model behavior in production.

This is a product-facing modeling role. Research depth matters, but success is measured by improvements that survive contact with production and create better guest, restaurant, and business outcomes. You will work closely with product, full-stack, infrastructure, and customer-facing engineers to move from hypothesis to experiment to reliable deployment.

What you’ll own
  • Develop modeling and experimentation strategies for high-impact agent problems in voice, language, reasoning, ordering, multilingual behavior, and multimodal understanding.
  • Build rigorous offline and online evaluations that measure task completion, accuracy, safety, latency, cost, conversational quality, and business outcomes.
  • Create and maintain representative datasets from simulations, human annotation, production feedback, and difficult edge cases while protecting sensitive data.
  • Evaluate frontier and open-source models and make clear build, buy, route, prompt, fine-tune, or distill decisions.
  • Improve prompting, context construction, memory, tool-use policies, structured outputs, model routing, and fallback behavior.
  • Design fine-tuning, preference optimization, distillation, or other post-training work when it offers a measurable advantage over simpler methods.
  • Partner with speech and real-time engineers to improve ASR, TTS, turn-taking, interruption handling, pronunciation, multilingual behavior, and end-to-end latency.
  • Develop analysis tools that explain model failures, slice performance by scenario, detect regressions, and accelerate iteration.
  • Ship model changes with production guardrails, staged rollouts, monitoring, rollback paths, and clear quality gates.
  • Translate new research and model releases into concrete product opportunities and communicate tradeoffs to technical and non-technical partners.
  • Raise scientific and engineering standards through reproducible experiments, thoughtful reviews, and clear documentation.
  • 3+ years of industrial experience in relevant technical domain.
  • Strong machine learning foundations and hands-on experience developing or evaluating production AI systems.
  • Strong Python skills and experience with modern ML tooling such as PyTorch, JAX, Hugging Face, or equivalent systems.
  • Practical experience with LLMs, speech models, multimodal models, or agentic systems.
  • Ability to design reliable experiments, define useful metrics, analyze noisy results, and avoid optimizing against weak proxies.
  • Experience building datasets, evaluation harnesses, model services, or training and inference pipelines.
  • Strong software engineering judgment; your work is reproducible, tested, observable, and usable by other engineers.
  • Ability to connect modeling choices to product constraints including latency, cost, privacy, safety, and user experience.
  • Comfort operating in ambiguity and collaborating across research, engineering, product, and customer contexts.
  • AI-native working habits and genuine curiosity about new model capabilities and limitations.
  • Competitive Salary and Stock Option Plan.
  • Medical, dental, vision, retirement, leave, and disability benefits as applicable.
  • Family Leave
  • Short Term & Long Term Disability
  • Paid time off and company holidays.
  • Learning and development support.
#J-18808-Ljbffr