Who is AiDash?
AiDash is an AI-first vertical SaaS company on a mission to transform operations, maintenance, and sustainability in industries with geographically distributed assets by using satellites and AI at scale. With access to a continual, near real-time stream of critical data, utilities, energy, mining, and other core industries can make more informed decisions and build optimized long-term plans, all while reducing costs, improving reliability, and achieving sustainability goals.
AiDash is backed by top-tier investors, including Benhamou Global Ventures, National Grid Partners, Edison International, Schneider Electric
and Shell Ventures. To learn more about how AiDash is helping core industries become more resilient, efficient, and sustainable, visit www.aidash.com.
What will you do?
- Manage and execute projects from start to finish, including cross-functional project management, data collection, modelling and analysis, synthesis and communication of insights and recommendations to cross functional stakeholders.
- Collect, organize, interpret, and summarize Geospatial and Statistical data to contribute to the design and development of AiDash products
- Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products
- Identify areas of opportunity and influence execution of results via cross-functional participation to enable quick wins and continuous improvement
- Demonstrate good judgment in selecting methods and techniques for obtaining solutions
- Mentor Interns / Junior Data Scientists during onboarding and to deliver high quality throughput
What are we looking for?
- Bachelor's / Master’s Degree in Computer Science, Mathematics & Computing, Electrical Engineering or related field from premiere institutes with an experience ranging from 3 to 6 years
- Theoretical knowledge and understanding of Image Processing, Machine Learning and Deep Learning basics.
- Practical experience in Statistical, Computer vision & Machine Learning models i.e., Deep learning models.
- Extensive experience in writing computer programs in Python, and relevant Deep Learning frameworks (PyTorch / TensorFlow / Caffe / etc.)
What experiences make you a better candidate?
- Experience in deploying ML services to production.
- Docker, Kubernetes
- Knowledge of databases (HDFS, RDBMS, Key-Value storage, MongoDB, etc.)
- Experience in Deploying Machine Learning solutions and familiarity with the tech-stack (Docker, FastAPI, PySpark, Kubeflow, etc.)
- Hands on experience with the Cloud Environment (AWS / GCP, S3, Lambda, etc.)
- Following best programming practices, Object Oriented Programming, Documentation and Code Reviews
