Job Description

Job Description

Job Description

Vision Systems Researcher

Division: DATUM, Impac Exploration Services
Location: Oklahoma City (OK), Houston (TX), San Jose (CA)
Type: Full-Time

We're building computer vision systems for environments where most cameras fear to tread. While everyone else is teaching AI to recognize cats and faces, we're teaching it to see patterns in the physical world that determine million-dollar outcomes.

DATUM needs a computer vision researcher who gets excited about novel imaging challenges. You'll work with data streams no one's properly analyzed before, from sensors and imaging systems that weren't designed to play nicely with neural networks. The patterns you'll teach our models to recognize have real-world consequences—this isn't about optimizing click-through rates.

What You'll Build

• Vision systems that extract insights from unconventional imaging modalities
• Real-time analysis pipelines for streaming visual data in challenging conditions
• Integration frameworks for specialized imaging hardware
• Computer vision that works where GPS doesn't and WiFi won't

The Research Reality

• Your models might need to work with imaging modalities that barely exist yet
• You'll push the boundaries of what's possible with computational photography
• Sometimes you'll work with data from sensors originally designed for astronomy or medical imaging
• You might need to extract signal from what others consider noise

You're Our Person If

• You've pushed computer vision beyond standard benchmarks
• Unconventional imaging excites rather than intimidates you
• You can adapt academic approaches to messy real-world constraints
• You understand when to use classical CV vs. deep learning
• You've made models work with limited or unusual training data
• You see physical-world applications as the real challenge

Especially If

• You've worked with quantum imaging or single-photon detection
• You have experience with interferometric or holographic reconstruction
• You've built vision systems for extreme environments (deep sea, space, particle physics)
• You understand computational imaging beyond traditional cameras
• You've explored neuromorphic vision sensors or event-based cameras
• You're comfortable with terahertz imaging or other exotic wavelengths

Technical Foundations

We expect fluency in:

• Modern CV frameworks (PyTorch, TensorFlow, or similar)
• Both classical and deep learning approaches
• Real-time optimization and edge deployment
• Working with non-standard image formats and sensor data
• Building robust systems for production environments

Why This Hits Different

• Your models will analyze things no one's properly looked at before
• Real impact—your work directly affects critical operations
• Access to imaging hardware and datasets that don't exist elsewhere
• Freedom to pursue novel approaches, not just incremental improvements
• Collaboration with researchers pushing boundaries in other domains
• Problems that require genuine innovation, not just applying known solutions

Growth Trajectory

Start by solving specific vision challenges. Soon you'll be defining how entire industries should approach visual analysis. Publish papers on approaches others haven't imagined. Build IP that reshapes what's possible with computer vision.

When Meta or Apple tries to poach you for their AR/VR teams, they'll be impressed by problems you've solved that they haven't even encountered yet.

The Reality

You'll work with data that's messy, hardware that's temperamental, and constraints that academic papers ignore. You'll need to understand enough about our domain to know what patterns matter. You'll optimize for inference speed as much as accuracy.

But you'll also pioneer computer vision applications that don't exist anywhere else. You'll see your models make decisions that matter. You'll prove that the most interesting vision problems aren't on Instagram—they're in the physical world.

Ready to See Differently?

Show us computer vision work that went beyond standard datasets. Tell us about a time you made vision work in a challenging environment. Share your thoughts on where industrial computer vision is heading.

We're looking for someone who sees unconventional imaging challenges and thinks "finally, something interesting."

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