Role: AI & Data Engineering Intern
Employment Type: Intern (Who can join us in person in Bangalore for 6 months immediately.)
Educational Qualification: Currently pursuing or recently completed a Bachelor's degree in Computer Science, Machine Learning, Data Science, Engineering, Physics, or a related field.
Role Description:
We are seeking an AI & Data Engineering intern to support the development of Pixxel's geospatial intelligence platform for maritime and land domain awareness. This platform fuses multi-source satellite imagery and sensor data into a unified operational picture, enabling defense and national security missions to detect, monitor, and reason about activity across maritime and land environments. This is a hands-on internship where you will work across the full stack: from data ingestion and preprocessing pipelines, through AI model development, to analyst-facing interfaces that make geospatial intelligence actionable.
Responsibilities & Duties:
Data Pipelines & Infrastructure:
Design and build scalable data pipelines for ingestion, preprocessing, and fusion of heterogeneous geospatial data sources, including optical satellite imagery, SAR, and vessel tracking telemetry (AIS), enabling efficient handling of multi-sensor, multi-temporal datasets.
-
Establish consistent data standards and quality control processes across geospatial data feeds, ensuring alignment, georeferencing accuracy, and metadata integrity for downstream analytics.
-
Build infrastructure for near-real-time geospatial data workflows, supporting continuous ingestion, scene-level processing, chip generation, and dataset export for model training and inference.
-
Develop monitoring and evaluation tools to assess data pipeline performance, data quality, and throughput, ensuring reliable operation across large-area, persistent surveillance use cases.
AI & Machine Learning
Apply transformer architectures to geospatial problems, including object detection, classification, and scene understanding in overhead imagery across both maritime and land domains.
-
Develop and fine-tune vision-language models (VLMs) that enable natural language reasoning over geospatial data, allowing analysts to query, describe, and interpret imagery-derived insights through conversational or programmatic interfaces.
-
Explore diffusion model approaches for geospatial tasks, including image generation, super-resolution, and synthetic data augmentation to improve model performance in data-sparse or adversarial scenarios.
-
Build multi-modal fusion pipelines that combine optical imagery, SAR, AIS, and other sensor feeds to detect anomalous activity, classify vessel behavior, and identify changes in the operational environment.
-
Benchmark and validate models against ground truth datasets and operational evaluation metrics, iterating on architectures and training strategies based on performance feedback from analyst workflows.
Cross-Functional Responsibilities
Write clean, efficient, and maintainable Python code for data processing and model development. Contribute to shared utilities and machine learning libraries used across the team.
-
Collaborate closely with cross-functional teams by:
-
Providing feedback on data quality and annotation issues across geospatial datasets.
-
Partnering with the ML team on model evaluation and performance improvements.
-
Coordinating with data engineers to optimize ingestion and preprocessing pipelines.
-
Documenting datasets, models, pipelines, and technical processes comprehensively to ensure reproducibility and provide clear technical insights for team members and end users.
Desirable Skills & Certifications:
Strong programming skills in Python with hands-on experience using libraries and frameworks such as PyTorch, TensorFlow, NumPy, Pandas, or equivalent.
-
Solid understanding of deep learning fundamentals, including Convolutional Neural Networks (CNNs), attention mechanisms, transformer architectures, loss functions, optimization techniques, and evaluation metrics.
-
Familiarity with vision-language models (VLMs), diffusion models, or multi-modal learning, with coursework, projects, or research experience in any of these areas.
-
Practical experience or strong academic coursework in data pipelines, data processing, or data engineering workflows.
-
Basic understanding of the end-to-end machine learning lifecycle, including model training, evaluation, and deployment at scale.
-
Familiarity with geospatial or remote sensing data, including overhead imagery analysis, SAR, or vessel tracking datasets, is a plus but not required.
-
Ability to work independently on well-defined workstreams, take ownership of deliverables, and proactively seek guidance from senior scientists when needed.
-
Strong attention to detail, with an understanding that high-quality data is critical to model performance.
-
Eagerness to learn quickly, adapt to new challenges, and thrive in a mission-driven, fast-paced environment.
Candidate Acumen:
You will own end-to-end workstreams across two primary areas: (1) Data & Infrastructure - building scalable pipelines for ingestion and fusion of multi-source geospatial data (optical, SAR, AIS, and other sensor feeds), establishing data quality standards, and supporting near-real-time analytical workflows; and (2) AI/ML - applying transformer architectures, vision-language models, and diffusion techniques to maritime and land domain awareness problems, including object detection, anomaly detection, and multi-modal sensor fusion, as well as building the agentic interfaces that allow analysts to query and reason about geospatial intelligence outputs. This is a hands-on role that bridges data engineering and deep learning - you will work closely with senior scientists and ML engineers on the platform team.
Benefits:
Health insurance coverage
Unlimited leaves & flexible working hours
Role-based remote work and work-from-home benefit
Relocation assistance
Professional Mental Wellness services
Creche facility for primary caregivers (limited to India)
Employee Stock Options for all hires
Pixxel is a space data company and spacecraft manufacturer redefining Earth observation with hyperspectral imaging. The company’s first three commercial hyperspectral satellites—Fireflies—deliver imagery at 5-meter resolution and 135+ spectral bands, providing 50x richer detail than traditional Earth observation systems and unlocking insights across agriculture, climate, energy, environment, and more.
Once fully deployed, Pixxel’s constellation of 18-24 satellites will capture imagery across up to 250 bands in VNIR and SWIR ranges, with a 40 km swath and daily global revisit capability. Pixxel’s most unique strength is its full-stack approach, integrating every layer of the value chain from satellite hardware and manufacturing to AI-powered analytics.
Pixxel’s satellite constellation is complemented by Aurora, its in-house Earth Observation Studio that simplifies satellite imagery analysis and democratises remote sensing for all. Designed to make hyperspectral data more accessible, Aurora by Pixxel combines high-frequency imagery with AI-powered tools to generate actionable insights, even for users without technical backgrounds. The third pillar of Pixxel’s ecosystem is its in-house satellite manufacturing capability. Beyond building its own spacecraft, Pixxel also provides satellite systems and subsystems to other organisations. This dual capacity sets it apart in a sector where most companies focus on either payload design or data operations, but not both.
Pixxel’s team is young but deeply mission-aligned, with a culture rooted in curiosity, speed, and long-term thinking. As the company grows its constellation and expands Aurora, the focus remains on making space-based insights practical, scalable, and genuinely helpful so that the health of the planet becomes measurable and action becomes possible.
Pixxel was the only Indian startup selected for the Techstars Starburst Space Accelerator in Los Angeles and has been recognised in TIME’s Best Inventions of 2023, Fast Company’s Most Innovative Companies, and Via Satellite’s Top Innovators list.
Culture
Pixxel is an organization where we enable our employees to work on world-changing problems that they are passionate about, and a place where they can be their best selves day in and day out while ensuring they have fun every day.
Central to our employee-first ethos is a commitment to ensuring that every team member feels valued and heard. We nurture a healthy and supportive work environment where we prioritise well-being and growth in all aspects of life
