{"id":3833275,"url":"https://alion.io/job/alta-ares-ml-engineer-internship","title":"ML Engineer - Internship","company":{"id":2199932,"name":"Alta Ares","domain":"altaares.com","url":"https://alion.io/company/altaares","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":11,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":90,"computed_at":"2026-11-07T05:47:08Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Paris, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"DVC","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weights & Biases","optional":false}],"status":"live","first_seen_at":"2026-11-05T15:37:57Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-07T19:42:55Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About Alta Ares\nAlta Ares is an air defense Neoprime. We build AI-guided interceptors to counter drones and cruise missiles, along with the software platform that powers them.\nOur customers are NATO-aligned militaries and defense institutions, and our systems are regularly deployed during live exercises and operational demonstrations across Europe, the Middle East, and Asia.\nFounded in 2024, we have grown to 90 people, raised over $60M, and increased revenue 40× this year. We are now entering a new phase of international expansion, industrial scaling, fundraising, and product development.\nRole & Mission\nWe are looking for a motivated Machine Learning Engineer Intern to join our Data & AI team and contribute to the development of our end-to-end ML pipelines.\nYou will help improve how we train, evaluate and deploy computer vision models, working on internal AI infrastructure and model lifecycle management.\nThis internship is ideal for someone interested in applied machine learning, computer vision and MLOps, who wants to gain hands-on experience building reliable AI systems for real-world defence applications.\nKey Responsibilities\nModel training: Improve and optimise training pipelines for computer vision tasks, including object detection, segmentation and tracking.\n\nModel evaluation: Develop evaluation frameworks using standard metrics such as mAP, IoU, precision and recall, and automate experiment tracking.\n\nData management: Build reproducible workflows for dataset versioning, augmentation and preprocessing of large-scale image and video datasets.\n\nModel deployment: Contribute to deployment workflows for optimised AI models running on edge devices and embedded systems.\n\nMonitoring and reliability: Implement tools to monitor deployed models and assess their robustness and performance.\n\nDocumentation and collaboration: Work closely with the Data & AI team to document best practices and help build scalable ML infrastructure.\n\nCandidate Profile\nStrong foundations in Python, data science and machine learning.\n\nKnowledge of deep learning frameworks such as PyTorch or TensorFlow.\n\nAbility to analyse, visualise and preprocess large-scale image and video datasets.\n\nFamiliarity with experiment tracking tools such as MLflow or Weights & Biases, and/or data versioning tools such as DVC.\n\nUnderstanding of Docker, Git and cloud platforms such as AWS or GCP.\n\nAbility to work autonomously in a research and prototyping 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