Simulation & Modeling

Simulation & Modeling Engineer Jobs

3 jobs found

Today

Senior Synthetic Data Engineer - Autonomous Driving

NVIDIA Santa Clara, CA

Santa Clara, CA

Today

$184k - $357k/yr Full time Senior Autonomous Driving Simulation Cloud Data Engineering

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Job Description

NVIDIA is building simulation-driven capabilities for autonomous driving, and this role focuses on turning reconstructed driving worlds into high-quality synthetic data at production scale. As a Senior Synthetic Data Engineer, you will design simulation environments and synthetic data pipelines using NVIDIA Omniverse NuRec and Cosmos, with an emphasis on multi-sensor realism, dataset quality assessment, and robust pipeline operations.

This position is based in Santa Clara, CA on an onsite basis, with an expected compensation range of USD 184,000 - 356,500 per year. Experience requirements include 8+ years in relevant engineering and technical domains.

What you’ll do

Build, implement, and optimize tools to generate synthetic data for training different DRIVE deep learning networks, including simulated lidar, radar, camera/RGB-D, bounding boxes, object tracks, world models, segmentation, depth, scene semantics, and sensor metadata.
Develop lidar and radar sensor simulation workflows that run on NuRec reconstructed driving worlds and Cosmos-generated environments, covering sensor placement, calibration, material response, geometry handling, noise modeling, and scenario variation.
Develop a Cosmos world model to improve world generation, including controllable scenario generation, novel view synthesis, trajectory extrapolation, scene completion, quality triage, regression detection, and controllability evaluation.
Gather perception, planning, and deep learning DRIVE network requirements, then map them to existing synthetic data and sensor simulation features, adding new tools or improving performance when gaps are found.
Create dataset quality assessments and synthetic-real comparison procedures to evaluate sensor realism, annotation quality, distribution coverage, scenario diversity, and sim-to-real transfer for autonomous driving.
Set up, profile, and oversee large-scale NuRec, Cosmos, and sensor simulation pipelines in data center or cloud environments.
Debug end-to-end, cross-stack systems spanning sensors, reconstruction models, world models, simulation runtime, GPU workloads, distributed data services, and downstream autonomous-driving workloads.

Required qualifications

B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, Applied Math, Physics, or a related field (or equivalent experience).
8+ years of experience in computer graphics, computer vision, autonomous driving, sensor simulation, neural rendering, or physically-based sensor modeling, synthetic data generation, or closely related software engineering roles.
Strong skills in Python and C++, including experience building, debugging, profiling, and maintaining production-quality systems on Linux.
Solid mathematical foundation in linear algebra, geometry, and probability.
Familiarity with synthetic data annotations, data formats, dataset curation, data augmentation, and evaluation workflows for perception model training and validation.
Familiarity with deep learning workflows and modern ML tooling, with enough practical depth to translate network needs into synthetic data requirements and measurable quality criteria.
Experience with scalable engineering workflows, including Git, Docker, Kubernetes, CI/CD, distributed storage, and deployment in data centers or cloud environments.

Technologies

Python, C++, Linux, Git, Docker, Kubernetes, CI/CD
NuRec, Cosmos, NVIDIA Omniverse
Distributed storage, cloud, data center

Equity and benefits

You will also be eligible for equity and benefits.

Ways to stand out

Practical experience working directly with NVIDIA NuRec, Cosmos, world foundation models, Real2Sim systems, or autonomous-driving simulation and validation pipelines.
Experience in NuRec world reconstruction, neural rendering, including 3D Gaussian Splatting, NeRFs, or occupancy networks.
Deep lidar or radar simulation expertise, including ray tracing or ray casting, reflectance and intensity modeling, Doppler, radar cross-section, weather effects, occlusion, and sensor-specific noise models.
Experience developing synthetic data pipelines for autonomous driving, including closed-loop simulation, domain randomization, long-tail scenario mining, or sim-to-real transfer.
Familiarity with autonomous vehicle data pipelines and formats such as OpenDRIVE, HD maps, scenario formats, vehicle dynamics, or AV safety validation.

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25d ago

Machine Learning Engineer

Molex Austin, TX

Austin, TX

25d ago

$170k - $250k/yr Full time Python Artificial Intelligence Azure Gpu Compute

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Job Description

Molex is hiring a Machine Learning Engineer for an Austin, TX onsite role. This position focuses on building physics-informed surrogate models on Azure Machine Learning to predict engineering simulation outcomes from design parameters. The result is faster iteration and reduced reliance on full high-fidelity simulation, with models deployed, monitored, and improved over time.

Compensation: USD 170,000 - 250,000 per yearly

Experience: 10+ years

What you will be doing

Design and train surrogate models using approaches such as neural networks, Gaussian processes, gradient-boosted trees, and GNNs/PINNs on Azure GPU compute (ND/NC series).
Incorporate physics-informed constraints so predictions remain physically valid rather than purely statistical fits.
Create uncertainty and confidence scoring to determine which designs require full simulation validation, then retrain as new results arrive.
Deploy and version models through Azure ML endpoints and the model registry, with ongoing rolling drift monitoring.
Benchmark surrogate performance against full simulation to quantify speedups and support platform-level performance tuning.

What you will need

Extensive hands-on experience building, training, and deploying ML models in production, not limited to using pretrained APIs.
10+ years building ML for physical/engineering systems, including surrogate modeling, physics-informed ML, or scientific ML.
Strong Python skills with PyTorch or TensorFlow.
Understanding of engineering/physics fundamentals and simulation data formats relevant to your domain.
Experience with Azure Machine Learning (or a similar cloud ML platform).
Familiarity with uncertainty quantification, including Bayesian approaches and ensembling.

Benefits

Medical, dental, and vision coverage
Flexible spending and health savings accounts
Life insurance
AD&D (ADD) and disability coverage
Retirement benefits
Paid vacation/time off
Educational assistance
May include infertility assistance
Paid parental leave and adoption assistance

What will put you ahead

Direct experience with industry-standard EM or physics simulation tools
Geometric deep learning experience, including graph neural networks and mesh-based models for CAD data
Background in RF/high-speed electronics or interconnect design

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1mo ago

Corporate Operations Engineer

WaterBridge Resources Houston, TX

Houston, TX

1mo ago Closed

Full time Civil Engineering Data Analysis Data Processing

This position is no longer accepting applications (closed Sep 9, 2026).

Job Description

WaterBridge Resources is hiring a Corporate Operations Engineer in Houston, TX for an onsite full-time role. This position supports hydraulic modeling, system capacity planning, and the engineering standards that guide consistent, compliant delivery across pipeline and water infrastructure operations. The work also includes digital transformation through coding and automation of engineering workflows.

Responsibilities

Utilize and develop hydraulics software models to simulate pipeline and system behavior
Run short-term and long-term system capacity modeling and evaluate results
Identify system bottlenecks and develop scope for related optimization projects
Maintain continual hydraulic model stewardship by updating the standard hydraulic model with as-builts and confirming equipment specifications and capacities
Match in-model facilities to in-the-field real equivalents
Perform system modeling, surge analysis, and hydraulic calculations to support both new and existing infrastructure
Collect and analyze field and operational data to build and validate system models
Support development and implementation of corporate engineering standards to ensure consistency, quality, and compliance across projects
Provide technical leadership during estimation and design phases
Collaborate with project managers, field personnel, and design teams to align engineering solutions with functional and operational needs
Assist in implementing new technologies to improve engineering and operational workflows
Contribute to digital transformation through coding and automation of engineering workflows

Requirements

Bachelor’s degree in Petroleum, Civil, or Mechanical Engineering
2+ years of relevant experience
Intermediate coding experience in at least one: Python, SQL, VBA, MATLAB, or C++
Introductory experience in steady state hydraulic modeling

Technologies

Python, SQL, VBA, MATLAB, C++
Pipesim
AFT Fathom
Synergi Pipeline Simulator (SPS)
Synergi Liquid

Preferred Qualifications

Mechanical Engineering degree
Proficiency with one or more hydraulic modeling software tools (Pipesim, AFT Fathom, Synergi Pipeline Simulator (SPS), Synergi Liquid, or equivalent)
Introductory experience in water hammer / surge analysis
Experience in operational data gathering and analysis
Programming and scripting skills in SQL, Python, or VBA

Key Competencies

Strong analytical and technical modeling skills with attention to detail
Ability to collaborate effectively across project management, field, and design teams
Self-directed approach to identifying and resolving system issues
Comfort applying coding and automation skills to improve engineering workflows

Benefits

Medical, Dental, Vision, & Prescription Drug Coverage
Voluntary Life Insurance for Employee, Spouse, & Child(ren)
Employee Basic Life and AD&D Insurance – Company Paid
Short Term & Long Term Disability – Company Paid
401(k) or Roth 401(k) Retirement Plan, plus a company match
Flexible Paid Time Off
And many other benefits not listed here

Working Conditions

Operates in a professional and/or business casual office environment.

Position Type: Full-time

Location: Houston, TX (onsite)

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Simulation & Modeling Engineer Jobs

Senior Synthetic Data Engineer - Autonomous Driving

Machine Learning Engineer

Corporate Operations Engineer

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