Machine Learning Engineer

InCommon is hiring on behalf of Altair.

About the Company

Altair Infrasec Pvt. Ltd. is a deep-tech defence company building mission-critical systems for the Indian Armed Forces. Operating at the intersection of advanced engineering and real-world deployment, Altair develops end-to-end technologies across AI/ML, signal processing, aerospace, electronics, and systems engineering. With a strong focus on in-house capability and technical ownership, the team works on high-impact programs spanning naval, army, and air force applicationsdelivering complex, combat-relevant systems with speed and precision.

Role Overview

We are looking for a Signal Processing and Machine Learning Engineer to join our team working on advanced audio-based detection systems. The role involves developing algorithms and machine learning models on acoustic signals and automate detection, classification, and tracking of patterns. The engineer will work across the full pipeline including signal preprocessing, feature extraction, ML model development, deployment, and integration into Python-based applications.

Key Responsibilities

Signal Processing

• Develop and implement audio signal processing pipelines for time-series and spectral analysis.
• Work with spectrogram representations.
• Implement filtering and preprocessing techniques.
• Extract meaningful time-frequency related and other features from audio samples.

Machine Learning & AI

• Develop multi-modal models for detection and classification of sound events.
• Train and optimize models using frameworks such as PyTorch, or TensorFlow.
• Design feature engineering pipelines for pattern classification and anomaly detection.
• Evaluate and improve model performance through experimentation and validation.

Model Deployment

• Implement efficient inference pipelines for real-time audio anomaly detection.
• Package and distribute models for use across multiple devices or edge systems.
• Maintain version control and update mechanisms for ML models.

Software Development

• Build and maintain Python-based tools and applications for audio data analysis and ML workflows.
• Integrate ML models into interactive tools or dashboards (e.g., Streamlit-based systems).
• Develop utilities for dataset generation, labeling workflows, and model training pipelines.
• Optimize performance for large audio datasets or Live audio streams.

Required Qualifications

Bachelors Degree + 3yrs experience or Masters degree (preferred) + 1yr experience in :

• Electrical Engineering/Signal Processing
• Computer Science/Machine Learning OR related field

Technical Skills

• Strong Python programming skills
• Experience with Scientific/Signal processing libraries: NumPy, SciPy, Librosa, OpenCV
• Experience with ML/DL frameworks: Scikit-learn, PyTorch or TensorFlow
• Experience working with spectrograms and other audio features
• Knowledge of digital signal processing (DSP) fundamentals
• Experience with model training, evaluation, and deployment

Software Engineering

Familiarity with:

• Git
• Linux environments
• Containerization (Docker preferred)
• Ability to design modular and maintainable Python codebases

Preferred Skills and Experience

• 2 years or more with audio anomaly detection
• 2 years or more in building ML pipelines and their maintenance
• 2 years or more in edge deployment or distributed ML systems

Key Traits

• Strong analytical and problem-solving skills
• Ability to work with experimental data and noisy signals
• Comfortable working in research + engineering environments
• Ability to translate domain problems into ML solutions