{"id":1777966,"url":"https://alion.io/job/galaxeye-space-ai-research-intern-dil","title":"AI Research Intern - DIL","company":{"id":59381,"name":"GalaxEye Space","domain":"galaxeye.space","url":"https://alion.io/company/galaxeye-space","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"Early Careers","role_family":"Early Careers","seniority":"intern","employment_type":"internship","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":8000,"max_usd":16000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":768},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Git","optional":false},{"name":"Linux","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"Transformers","optional":false},{"name":"CLIP","optional":true},{"name":"GDAL","optional":true},{"name":"LLaVA","optional":true},{"name":"Qwen","optional":true},{"name":"Weights & Biases","optional":true}],"status":"live","first_seen_at":"2026-10-03T17:02:56Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-22T00:42:31Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":18},"description":"AboutGalaxEye\nGalaxEyeis an Indian space tech startup dedicated to pioneering multi-sensor imaging satellites, founded by IIT Madras students and alumni and incubated at IIT Madras. The company is developing the Drishti Mission - the world's first satellite with multi-sensor capabilities that deliver all-time, all-weather imagery from space, even during nighttime and in challenging conditions.GalaxEye'stechnology enables advanced geospatial analyses for governments, defense, and industries worldwide.\nOur AI team buildscutting-edgedeep learning systems that extract intelligence from high-resolution EO and SAR satellite data. This internship offers an opportunity to work on proprietary datasets and contribute to novel research problems at the intersection of computer vision, multimodal AI, and remote sensing.\nWhat You'll Work On\nYou'llwork on challenging research problems in satellite image understanding and multimodal geospatial AI. Depending on your background and interests, you may contribute to one or more of the following areas:\nSAR-to-EO image translation using generative models such as diffusion models and GANs.\nVision-Language Models (VLMs) for understanding, retrieval, reasoning, and interaction with EO and SAR imagery.\nFoundation models for remote sensing, including representation learning, multimodal fusion, segmentation, detection, and large-scale pretraining on satellite imagery.\nThis is a research-focused role whereyou'llbe expected to read deeply, experiment rigorously, and contribute novel ideas rather than simply implement existing solutions.\nWhat You'll Do\nConduct structured literature surveys onstate-of-the-artdeep learning, multimodal learning, and remote sensing research.\nReproduce and benchmark recent research papers on EO and SAR datasets.\nTrain, fine-tune, and evaluate deep learning models on proprietary high-resolution satellite imagery.\nDesign and execute rigorous experiments with proper tracking, ablations, and analysis.\nDevelop and adapt architectures including CNNs, Vision Transformers, diffusion models, GANs, and multimodal foundation models.\nAnalyze model performance,identifyfailure modes, and propose improvements.\nCollaborate closely with researchers and engineers, present findings, and contribute to technical reports and research publications.\nRequirements\nStrong Python andPyTorch.\nSolid foundations in deep learning and modern computer vision.\nExperience with one or more of the following:\nTransformers and Vision Transformers.\nGenerative models (Diffusion Models, GANs, VAEs).\nVision-Language Models or multimodal learning.\nFamiliarity with Linux, Git, and GPU-based training workflows.\nStrong experimental and research mindset.\nGood to Have\nExperience with EO, SAR, or geospatial datasets.\nFamiliarity with Sentinel-1, Sentinel-2, Landsat,SpaceNet,BigEarthNet, SEN12MS, or related datasets.\nExperience with CLIP, BLIP,LLaVA,SigLIP, Qwen-VL, or similar multimodal models.\nExposure to raster geospatial data tools such as GDAL orrasterio.\nExperience withexperiment tracking tools such asMLflowor Weights & Biases.\nPublications, research projects, or open-source contributions in computer vision, generative AI, multimodal AI, or remote sensing.\nBenefits\nAccess to proprietary high-resolution SAR and EO satellite datasets that are unavailable publicly.\nMentorship from researchers and engineers from top institutions.\nExposure to the full AI research lifecycle-from problem formulation and data preparation to model development, evaluation, and reporting.\nOpportunity to contribute tocutting-edgeresearch in multimodal geospatial AI.\nStrong performers may have opportunities to co-author publications and be considered for full-time research roles 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