2027 Internship Simulation Engineer, Neural Rendering

Bedrock Robotics
San Francisco, CA
On-siteCareer-pivot friendly

Who this role is best for

A natural match if you have experience with neural rendering and simulation engines.

Best fit for

  • Candidates with academic or industry experience in neural rendering and 3D graphics fundamentals
    — “Solid understanding of 3D graphics fundamentals: rendering pipelines, scene representations, camera models, and coordinate systems”
  • Individuals comfortable with messy, unstructured real-world data and domain-specific challenges
    — “Comfort with real-world data — construction sites are messy, dusty, and nothing like an indoor dataset”
  • Those who have worked on simulation engines or synthetic data generation for robotics or autonomous systems
    — “Experience with simulation engines (Unreal, Unity, NVIDIA Isaac Sim, or similar)”

Things to consider

  • The role demands working with real-world data that is unclean and complex compared to standard datasets
    — “construction sites are messy, dusty, and nothing like an indoor dataset”
  • The internship is likely to be in-person, given the emphasis on physical-world problem-solving
    — “This is where algorithms meet steel-toed boots”

How to stand out

  • Highlight experience with neural rendering techniques like NeRF or Gaussian splatting in your resume
    — “Research, implement, and benchmark neural rendering methods (NeRF, 3D Gaussian splatting, or related techniques)”
  • Showcase projects that involved training models on real-world data with complex visual conditions
    — “Train models on real-world site data captured by our fleet and evaluate visual fidelity”
  • Demonstrate ability to integrate rendering outputs into simulation pipelines or similar systems
    — “Integrate neural rendering outputs into the simulation pipeline”
  • Emphasize your background in addressing domain-specific challenges in dynamic environments
    — “Identify and address failure modes: dynamic objects, deformable terrain, dust, harsh lighting”
  • Include documentation or evaluation tools you've built for visual or performance metrics
    — “Build evaluation metrics and tooling that quantify how well rendered scenes match real fleet data”
Pace · SteadyCollaboration · MediumAutonomy · MediumDecision Impact · Individual

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • implement neural rendering methods
  • train models on real-world data
  • integrate neural rendering into simulation pipeline
  • build evaluation metrics
Typical background
BS, MS, or PhD in computer science, computer graphics, robotics

Skills & requirements

Required

Neural Rendering3D GraphicsPythonPyTorchReal-world Data HandlingSimulation

Preferred

Simulation EnginesAutonomous Vehicle SimulationSynthetic Data Generation

Stack & domain

PythonPyTorch3D GraphicsRendering PipelinesScene RepresentationsCamera ModelsCoordinate SystemsNeural Scene RepresentationsNerfGaussian SplattingNeural Radiance FieldsResearchImplementationBenchmarkingModel TrainingEvaluation MetricsToolingFailure Mode IdentificationAIAutonomyConstructionSimulationNeural Rendering

About the role

Original posting from Bedrock Robotics via Ashby

JOIN THE TEAM BRINGING ADVANCED AUTONOMY TO THE BUILT WORLD

At Bedrock, we're moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects.

We're not here debating the future of AI. We're deploying it in the real world. In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.

ABOUT THE ROLE & TEAM

Before an autonomous excavator digs its first trench on a new site, it's already dug thousands in simulation. The Simulation team builds the virtual environments our autonomy stack trains and tests against — and the closer sim looks and behaves like the real world, the faster we move. Neural rendering is the next step: replacing hand-authored assets and approximations with learned representations that capture the visual complexity of real jobsites — dust, lighting, deformable terrain, heavy equipment in motion. As our Simulation intern, you'll push neural rendering techniques into our sim pipeline and measure whether they actually close the visual gap that matters for downstream autonomy performance.

WHAT YOU'LL DO

  • Research, implement, and benchmark neural rendering methods (NeRF, 3D Gaussian splatting, or related techniques) for generating realistic construction-site imagery within our simulation stack
  • Train models on real-world site data captured by our fleet and evaluate visual fidelity, temporal consistency, and render speed
  • Integrate neural rendering outputs into the simulation pipeline so perception and planning teams can train and test against them
  • Build evaluation metrics and tooling that quantify how well rendered scenes match real fleet data — and whether that improvement transfers to autonomy performance
  • Identify and address failure modes: dynamic objects, deformable terrain, dust, harsh lighting, and other construction-specific challenges
  • Document findings, limitations, and a recommendation on where neural rendering should (and shouldn't) replace traditional sim assets

WHAT WE'RE LOOKING FOR

REQUIRED

  • Currently pursuing a BS, MS, or PhD in computer science, computer graphics, robotics, or a related field — or bringing equivalent research or industry experience
  • Strong Python and hands-on experience with PyTorch (or equivalent)
  • Solid understanding of 3D graphics fundamentals: rendering pipelines, scene representations, camera models, and coordinate systems
  • Familiarity with neural scene representations (NeRF, Gaussian splatting, neural radiance fields, or related methods)
  • Comfort with real-world data — construction sites are messy, dusty, and nothing like an indoor dataset

PREFERRED

  • Published work or substantial project experience in neural rendering, novel view synthesis, or differentiable rendering
  • Experience with simulation engines (Unreal, Unity, NVIDIA Isaac Sim, or similar)
  • Background in autonomous vehicle simulation or synthetic data generation
  • Familiarity with C++ and GPU programming (CUDA, OpenGL, Vulkan)

Bedrock Robotics is an Equal Opportunity Employer

We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.

Reasonable Accommodations

We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.

Source: Bedrock Robotics careers (Ashby)

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