Software Engineer III - Simulation CV/ML Engineer

Spectraforce Technologies; Sunnyvale (CA); Híbrido; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Spectraforce Technologies, Inc. seeks a Software Engineer III - Simulation CV/ML Engineer in Sunnyvale, CA. Hybrid role with 3 days onsite.

You will run and iterate on camera/sensor simulation pipelines to generate synthetic datasets and support ML training and evaluation using the data. Requirements include a Bachelor's in CS, 5+ years in software engineering with ML infra, strong Python and C++, and camera/sensor simulation fundamentals.

Formación

• Bachelor's degree in computer science or related field.
• 5+ years of software engineering experience focusing on ML infrastructure design.
• 5+ years' experience in Python and C++.
• Camera & sensor simulation fundamentals: calibration and setup
• Sensor modeling: noise, 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 metrics and translate to dataset changes
• 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

Responsabilidades

• 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 generated synthetic data
• Configure simulation scenes and sensor parameters to match specifications
• Validate and quality-check generated data before hand-off
• Maintain and improve simulation tooling and dataset generation scripts

Conocimientos

Python

C++

ML infrastructure design

ML training & evaluation

Linux

Git / Source control

PyTorch

Dataset generation

Camera simulations

Sensor simulations

IS P knowledge

Educación

Bachelor's degree in computer science or related field

Herramientas

Linux

Git

PyTorch

Descripción del empleo

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