Vidar Systems

Vidar Systems is a Ukrainian startup in the field of acoustic technologies, operating at the intersection of defense and security. We develop acoustic systems that use sound to determine the location of hostile objects, including artillery and drones.

About the Role
Become a core member of our high-impact engineering team and architect the AI systems that protect Ukraine’s frontline defense. You will own the full lifecycle of ML solutions—from design to edge deployment—in a mission-critical acoustic reconnaissance environment.

What You’ll Do

• Design, implement, evaluate, and optimize ML/DL models for acoustic detection and classification tasks.

• Collect, clean, and preprocess datasets for model training and evaluation.

• Write modular, testable code for preprocessing, model inference, and automation tasks.

• Develop and maintain robust data pipelines to support efficient model training and evaluation workflows.

• Develop strategies for model quantization and compression to ensure high performance on resource-constrained hardware.

What You Need

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.

• 2+ years of professional Python experience in ML/DL production applications.

• Hands-on expertise in designing, training, and integrating ML systems into production environments.

• Deep experience with TensorFlow, PyTorch, PyTorch Lightning, scikit-learn, NumPy, and Pandas.

• Strong analytical, communication, and problem-solving skills; ability to thrive and execute independently in a high-stakes, fast-paced startup environment.

• Good technical English.

Nice to Have

• C/C++ experience (especially valuable for our next-generation systems).

• Background in the audio domain or digital signal processing (DSP).

• Proficiency in training unsupervised learning models.

• Experience with the optimization and deployment of ML models on edge devices.

Our Recruitment Process

1. Intro call with recruiter — 45 min

2. Technical interview with ML Lead — 90 min

3. Test task — 4–6 hours

4. Final interview with ML Lead and CTO — 60 min

Why Join Us?

• High Autonomy: Shape the direction of our software solutions with minimal oversight and maximum ownership.

• Innovation at the Edge: Contribute to military acoustic reconnaissance systems at the forefront of defense tech, redefining ML in harsh, real-world acoustic environments.

• Flexible Work Options: Benefit from adaptable arrangements and a culture that truly values your input and well-being.

Vidar Systems is a Ukrainian startup in the field of acoustic technologies, operating at the intersection of defense and security. We develop acoustic systems that use sound to determine the location of hostile objects, including artillery and drones.

About the Role
Become a core member of our high-impact engineering team and architect the AI systems that protect Ukraine’s frontline defense. You will own the full lifecycle of ML solutions—from design to edge deployment—in a mission-critical acoustic reconnaissance environment.

What You’ll Do

• Design, implement, evaluate, and optimize ML/DL models for acoustic detection and classification tasks.

• Collect, clean, and preprocess datasets for model training and evaluation.

• Write modular, testable code for preprocessing, model inference, and automation tasks.

• Develop and maintain robust data pipelines to support efficient model training and evaluation workflows.

• Develop strategies for model quantization and compression to ensure high performance on resource-constrained hardware.

What You Need

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.

• 2+ years of professional Python experience in ML/DL production applications.

• Hands-on expertise in designing, training, and integrating ML systems into production environments.

• Deep experience with TensorFlow, PyTorch, PyTorch Lightning, scikit-learn, NumPy, and Pandas.

• Strong analytical, communication, and problem-solving skills; ability to thrive and execute independently in a high-stakes, fast-paced startup environment.

• Good technical English.

Nice to Have

• C/C++ experience (especially valuable for our next-generation systems).

• Background in the audio domain or digital signal processing (DSP).

• Proficiency in training unsupervised learning models.

• Experience with the optimization and deployment of ML models on edge devices.

Our Recruitment Process

1. Intro call with recruiter — 45 min

2. Technical interview with ML Lead — 90 min

3. Test task — 4–6 hours

4. Final interview with ML Lead and CTO — 60 min

Why Join Us?

• High Autonomy: Shape the direction of our software solutions with minimal oversight and maximum ownership.

• Innovation at the Edge: Contribute to military acoustic reconnaissance systems at the forefront of defense tech, redefining ML in harsh, real-world acoustic environments.

• Flexible Work Options: Benefit from adaptable arrangements and a culture that truly values your input and well-being.