AI Deep Learning Scientist

Educational Qualification: Education: Masters or PhD in Computer Science, Machine Learning, AI, Engineering, or a related technical field.

Work Experience : Experience: 4-6 years of experience in machine learning based data product research and development in addition to relevant educational background in the field of Computer Science, Engineering, Machine Learning etc.

Role Description

We are seeking an AI Scientist to join our analytics team. This role focuses on the development of innovative machine learning and deep learning models that unlock the full potential of Pixxels hyperspectral data. You will work on impactful, data-driven projects aimed at solving complex challenges using state-of-the-art technology and methodologies.

As a key contributor to Pixxels analytics vision, you will:

• Leverage state-of-the-art AI techniques to address complex challenges in imaging analytics, data fusion, and large-scale data processing.

• Develop multimodal AI models that integrate hyperspectral data with other sensor modalities like radar, LiDAR, and weather datasets, enabling actionable insights for clients across diverse industries.

• Work closely with cross-functional teams, translating business and scientific objectives into AI-powered solutions that are scalable, efficient, and impactful.

Responsibilities & Duties :

• AI Model Development: Design and implement advanced AI/ML models for classification, prediction, segmentation, and anomaly detection using Pixxels hyperspectral data and multimodal datasets.

• Multimodal Data Fusion: Integrate diverse data sources, such as hyperspectral, radar, LiDAR, and ancillary datasets, to enhance feature extraction, accuracy, and scalability.

• Algorithm Optimization: Develop computationally efficient algorithms that can handle large-scale, high-dimensional datasets and deploy them in production environments.

• R&D Leadership: Research and implement state-of-the-art techniques, including Transformer models, GANs, self-supervised learning, and other emerging techniques, to stay ahead in AI innovation.

• Cross-Functional Collaboration: Work with domain experts (e.g., hyperspectral scientists, environmental specialists) to understand the data and define project objectives, translating business problems into robust AI models.

• Communication & Presentation: Clearly explain complex AI concepts, model outputs, and research findings to technical and non-technical stakeholders.

Skills and Experience Required:

• Technical Expertise:

• Proficiency in advanced machine learning and deep learning architectures (e.g., CNNs, RNNs, Transformers, GANs, LSTMs).

• Strong background in Python and frameworks such as PyTorch, TensorFlow, or PyTorch Lightning.

• Experience in developing AI models for complex datasets. Experience with imaging data (e.g., hyperspectral, medical, drone, or satellite imagery), is not required, but would be beneficial.

• Solid understanding of key principles in multimodal data fusion, computer vision, and large-scale data processing.

• Communication & Collaboration:

• Strong communication skills to present findings, teach concepts, and collaborate effectively with non-AI experts.

• Ability to work cross-functionally with data scientists, engineers, and domain specialists .

• R&D Mindset:

• Proven experience in implementing cutting-edge research techniques and staying up-to-date with advancements in AI.

Candidate Acumen

Benefits:

• Comprehensive insurance coverage for you and your family.

• Free access to mental health professionals and paid sick leave.

• Benefits like vaccination drives and more.

• Flexible working hours.

• Opportunity to work with top scientists and professionals in space technology.