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We are looking for an AI/ML Engineer to join our team. If you are passionate about machine learning, and data-driven solutions, and have experience in applying AI to real-world problems, wed love to hear from you!

Key Responsibilities:

1. Design, develop, and deploy AI models for fleet management, including predictive analytics for vehicle maintenance, route optimization, and driver behavior analysis.
2. Collaborate with full-stack developers to integrate AI models into the web platform and ensure seamless deployment.
3. Work with real-time data streams from tracking devices to process, analyze, and build machine learning pipelines.
4. Implement algorithms for data processing, anomaly detection, and optimization tailored to the business needs of fleet management.
5. Pre-process and analyze large datasets to identify patterns and insights that can improve operational efficiency.
6. Build machine learning models using supervised and unsupervised learning techniques for key functionalities like predictive maintenance and driver behavior scoring.
7. Evaluate, fine-tune, and deploy models to ensure high performance and scalability.
8. Stay updated with the latest advancements in machine learning technologies and recommend improvements to current processes.

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
• Minimum 2 years of hands-on experience with machine learning and AI algorithms.
• Strong programming skills in Python (libraries like TensorFlow, PyTorch, Scikit-learn, etc.).
• Proficient in data manipulation and analysis tools (e.g., Pandas, NumPy).
• Experience working with real-time data or time-series data is a plus.
• Understanding of microservices architecture and APIs integration.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and experience deploying models in production environments.
• Strong problem-solving skills and the ability to work both independently and in collaboration with other team members.

Preferred Skills:

1. Experience with containerization technologies like Docker.
2. Familiarity with Kubernetes for managing scalable AI applications.
3. Knowledge of data pipelines and data engineering concepts.
4. Experience in the fleet management or logistics industry is a plus.

Other Details:

• Work Mode: Onsite - Full Time
• Experience: 2-5 years
• Days: Monday to Friday
• Timing: 10am-7pm

Skills:

Frontend Engineering, Engineering Analysis, Programming Languages, Project Engineering, Artificial Intelligence Knowledge,