Software Engineer III - Simulation CV/ML Engineer

Spectraforce Technologies, Inc.; Sunnyvale (CA); Hybrid; USD 150,000 - 220,000; Full time

Job summary

Spectraforce Technologies, Inc. seeks a Software Engineer III - Simulation CV/ML Engineer in Sunnyvale, CA, on a hybrid schedule (3 days onsite).

You will run camera/sensor simulations to generate synthetic data, support ML training, and optimize data pipelines for fast iteration with tight deadlines. Required are 5+ years in software engineering focused on ML infrastructure, strong Python/C++ skills, and experience with PyTorch.

Qualifications

• Bachelor's degree in computer science or a related field.
• 5+ years of experience in software engineering with a focus on ML infrastructure design.
• 5+ years' experience in Python and C++.
• Camera intrinsic/extrinsic setup and calibration.
• Sensor modeling: noise sources, conversion gain, quantum efficiency, read/shot noise.
• Basic understanding of ISP and image formation.
• ML training & evaluation.
• Experience running ML training/evaluation workflows (PyTorch preferred).
• Able to interpret model metrics and translate them back into dataset changes.
• Data handling: comfortable with large-scale dataset generation, storage, and versioning.
• Familiarity with Linux dev environments and source control.
• Experience building ML models and pipelines.
• Understanding how camera simulations work.
• Previous AI experience to develop ML architectures.

Responsibilities

• Run and iterate on camera/sensor simulation pipelines to generate synthetic datasets on demand.
• Deliver training/evaluation data to camera architects and ML teams under tight timelines.
• Support ML algorithm training and evaluation using the generated synthetic data - run training jobs, produce evaluation metrics, and iterate on dataset composition based on model performance.
• Configure simulation scenes and sensor parameters to match customer/architect specifications.
• Validate and quality-check generated data before hand-off.
• Maintain and improve simulation tooling and dataset generation scripts.

Skills

Python

C++

ML infrastructure

Camera simulation

ML training

PyTorch

Data handling

Linux

Source control

ML models & pipelines

Education

Bachelor's degree in computer science

Tools

Blender

Unreal

Unity

Job description

Job Title: Software Engineer III - Simulation CV/ML Engineer

Duration: 12 Months

Location: Sunnyvale, CA (hybrid - 3 days onsite)

Responsibilities:

• Run and iterate on camera/sensor simulation pipelines to generate synthetic datasets on demand
• Deliver training/evaluation data to camera architects and ML teams under tight timelines
• Support ML algorithm training and evaluation using the generated synthetic data - run training jobs, produce evaluation metrics, and iterate on dataset composition based on model performance
• Configure simulation scenes and sensor parameters to match customer/architect specifications
• Validate and quality-check generated data before hand-off
• Maintain and improve simulation tooling and dataset generation scripts

Top 3 must-have HARD skills:

Minimum Qualifications

• Bachelor's degree in computer science or a related field.
• Minimum 5+ years of experience in software engineering, with a focus on ML infrastructure design.
• 5+ years' experience in Python and C++.
• Camera & sensor simulation fundamentals:
• Camera intrinsic/extrinsic setup and calibration
• Sensor modeling: noise sources, conversion gain, quantum efficiency, read/shot noise
• Basic understanding of ISP and image formation
• ML training & evaluation
• Experience running ML training/evaluation workflows (PyTorch preferred)
• Able to interpret model metrics and translate them back into dataset changes
• Data handling: comfortable with large-scale dataset generation, storage, and versioning
• Familiarity with Linux dev environments and source control
• Experience building ML models and pipelines
• Understanding how camera simulations work
• Previous AI experience to develop ML architectures

Good to have skills:

Preferred Qualifications

• Experience with rendering engines (Blender, Unreal, Unity) or in-house simulation frameworks
• Optical/imaging background (radiometry, PSF, MTF)
• Prior experience with camera/ISP tuning or perception model development

Typical Day in the Role:

Responsibilities

• Run and iterate on camera/sensor simulation pipelines to generate synthetic datasets on demand
• Deliver training/evaluation data to camera architects and ML teams under tight timelines
• Support ML algorithm training and evaluation using the generated synthetic data - run training jobs, produce evaluation metrics, and iterate on dataset composition based on model performance
• Configure simulation scenes and sensor parameters to match customer/architect specifications
• Validate and quality-check generated data before hand-off
• Maintain and improve simulation tooling and dataset generation scripts

Minimum Qualifications:

• Bachelor's degree in computer science or a related field.
• Minimum 5+ years of experience in software engineering, with a focus on ML infrastructure design.
• 5+ years' experience in Python and C++.
• Camera & sensor simulation fundamentals:
• Camera intrinsic/extrinsic setup and calibration
• Sensor modeling: noise sources, conversion gain, quantum efficiency, read/shot noise
• Basic understanding of ISP and image formation
• ML training & evaluation
• Experience running ML training/evaluation workflows (PyTorch preferred)
• Able to interpret model metrics and translate them back into dataset changes
• Data handling: comfortable with large-scale dataset generation, storage, and versioning
• Familiarity with Linux dev environments and source control
• Experience building ML models and pipelines
• Understanding how camera simulations work
• Previous AI experience to develop ML architectures

Preferred Qualifications:

• Experience with rendering engines (Blender, Unreal, Unity) or in-house simulation frameworks
• Optical/imaging background (radiometry, PSF, MTF)
• Prior experience with camera/ISP tuning or perception model development

Interview process:

• 1 technical interview
• 1 Screening interview
• 30 mins for Screening and 45 mins for technical