AI Engineer

Responsibilities

• Be fully hands-on and work closely with the founders and product team to identify and implement AI/ML solutions that drive product innovation.
• Design, develop, and deploy scalable machine learning models and pipelines from proof-of-concept to production using cutting-edge technologies.
• Work with large and complex geospatial datasets, performing data cleaning, feature engineering, and model training.
• Work in a dynamic, collaborative, transparent, non-hierarchical culture.
• Work in collaborative, fast-paced, and value-driven teams to build innovative products.
• Help to grow the next generation of developers and have a positive impact on the industry.
  

Requirements

• Preferred educational background is B. E/B. Tech/M. C. A degree in Computer Science, Data Science, or a related field. However, this doesn't stand as a barrier if you are a passionate coder.
• Work Experience around 1-4 years in a relevant AI/ML or Data Science role.
• Strong hands-on experience with Python and essential AI/ML libraries (e. g., TensorFlow, PyTorch, scikit-learn).
• Proven experience in developing, evaluating, and optimizing various machine learning models (e. g., CNNs, RNNs, Transformers).
• Solid understanding of data structures, algorithms, and relational databases.
• Exposure to the geospatial domain, like Geo servers, PostGIS, libraries like Open Layers and Map Libre, Google map APIs, Open Street Maps, etc., will be a big add-on.
  

Nice To Have Qualifications

• Experience with MLOps practices, including continuous integration and deployment (CI/CD) for ML models.
• Experience with cloud platforms (AWS, Azure, GCP) for deploying and managing ML applications.
• Knowledge of big data technologies such as Spark, Hadoop, or Kafka.
• Product and customer-centric mindset.