Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal: ask the recruiter.
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No government sponsor record hereNo government sponsor record covers this employer in this country.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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Can’t check pay against the visa rulesWe don’t have visa salary rules for this country yet.
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Confirmed live todayWhen a source last listed this job as open.
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Before you apply
Sponsorship unknown
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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About the role
• We are seeking a talented Applied AI/ML Engineer to develop sophisticated models that leverage both visual and time-series data.
• In this role, you will focus on designing and implementing advanced algorithms to extract meaningful patterns, make accurate predictions, and solve complex analytical challenges.
• Your primary responsibility will be hands-on model development (for deploying in to automotive domain), from data analysis and feature engineering to training and evaluation.
• Key Responsibilities: Advanced Model Development Design, build, and validate machine learning models for a variety of complex tasks, including: Computer Vision: Object Detection, Image Segmentation, Facial Analysis, and Classification.
• Time Series Analysis: Forecasting, Anomaly Detection, and Classification of sequential data.
• Multi-Modal Modeling: Fusing visual and temporal data to create more powerful predictive models.
• Algorithm Implementation and train a wide range of models, including Deep Learning architectures (CNNs, Transformers, LSTMs, GRUs) and traditional statistical methods (e.g., ARIMA, Prophet).
• Stay current with state-of-the-art techniques and apply them to our unique datasets.
• Data Analysis & Feature Engineering Conduct in-depth exploratory data analysis to understand data characteristics and identify predictive signals.
• Develop and implement novel feature engineering techniques tailored to both image and time-series data.
• Model Optimization & EvaluationFocus on building computationally efficient models.
• Rigorously evaluate model performance using appropriate metrics and validation strategies to ensure robustness and accuracy.
• Optimize model architecture and hyperparameters to achieve desired performance targets.
B-Tech
10+
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