Sonatus is a well-funded, fast-paced, and fast-growing company whose technologies and software help automakers build dynamic software-defined vehicles. With two generations of solutions already on the road with a top global OEM, our vehicle and cloud software solutions are at the forefront of the digital transformation of vehicles. The Sonatus team is a talented and diverse collection of technology and automotive specialists hailing from many of the most prominent companies in their respective industries.

We are looking for a Machine Learning Engineer Intern to support the development of ML models for automotive software applications. This role focuses on data-driven insights, predictive analytics, and anomaly detection in vehicle data. As an intern, you will gain hands-on experience in data preprocessing, model training, and evaluation, working closely with experienced engineers to apply ML techniques in a real-world automotive context.

Applications are open until March 10th. Interviews will take place at the end of March/Early April. Internships will begin in June and end in August 2025.

Key Responsibilities:

• Data Processing & Exploration:
• Assist in collecting, cleaning, and preprocessing vehicle sensor, telematics, and diagnostic data.
• Perform exploratory data analysis (EDA) to understand trends and patterns.
• Machine Learning Model Development:
• Implement and experiment with ML algorithms for predictive analytics, anomaly detection, and time-series forecasting.
• Train and test models using libraries like Scikit-learn, TensorFlow, or PyTorch under guidance.
• Model Evaluation & Tuning:
• Help analyze model performance using metrics such as accuracy, precision, recall, and RMSE.
• Assist in hyperparameter tuning and model optimization.
• Collaboration & Learning:
• Work alongside software and ML engineers to understand real-world challenges in automotive ML.
• Document findings, experiments, and results clearly.

Required Qualifications:

• Pursuing a Bachelor's or Master’s degree in Computer Science, Computer engineering, Electrical engineering, or other related fields.
• Programming: Basic proficiency in Python (experience with Pandas & NumPy is a plus).
• Machine Learning: Understanding of basic ML concepts like regression, classification, and clustering.
• Data Handling: Familiarity with data preprocessing, feature engineering, and visualization (e.g., Matplotlib, Seaborn).
• Statistics & Mathematics: Foundational knowledge of probability, linear algebra, and time-series analysis.
• Ability to work from our Sunnyvale HQ 3 days a week.

Preferred Skills (Bonus, but Not Required):

• Familiarity with automotive data formats (OBD-II, CAN bus, telematics).
• Exposure to cloud computing (AWS, GCP, or Azure) for ML workloads.
• Basic understanding of embedded systems and real-time data processing.

Who Should Apply?

If you are a student or recent graduate with a passion for machine learning and automotive technology, eager to learn and contribute in a real-world setting, we encourage you to apply!

Sonatus Perks include:

• Complimentary lunches, snacks and beverages during on-site working days

The posted salary range is a general guideline and represents a good faith estimate of what Sonatus ("Company") could reasonably expect to pay for this position. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, geographic location and external market pay for comparable jobs. The Company reserves the right to modify this range in the future, as needed, as market conditions change.