{"id":1288770,"url":"https://alion.io/job/2-sofutoueaenjiniaperception-odel-eployment-nd-ntegration-ngineeryewuweituo","title":"【ソフトウェアエンジニア】Perception Model Deployment and Integration Engineer/業務委託","company":{"id":2155853,"name":"T2","domain":"t2.auto","url":"https://alion.io/company/t2-auto","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"HERP","truth_index":null},"role":"Backend","role_family":"Backend","seniority":null,"employment_type":"freelance","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tokyo, 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Engineer/業務委託\nDescription\nトラックを用いたレベル4自動運転システムの開発を担います。自動運転は周囲の環境を高精度に認識し安全かつ快適な走行経路に車両を導くというタスクです。様々な技術的チャレンジがあり、機械学習、数理最適化、シミュレーション、組み込みシステムなど幅広い分野で人材を募集しています。\nPerception チームでは現在 Camera・LiDAR・Radar を用いたマルチモーダル3次元物体検出器を開発しており、開発したモデルは既に実車両にデプロイされ、公道走行に用いられております。T2ではデータ収集、アノテーションパイプライン、モデル開発、デプロイまで全て内製で開発しており、機械学習インフラにも投資がされております。\n本チームではこの3次元物体検出器にトラッキング・Predictionおよび周辺環境認識含めた機能の開発を担っています。このポジションでは、特に車載のエッジデバイス上でこれらの機能を実現する高品質・高効率なソフトウェアコンポーネントの設計・開発・評価に携わっていただきます。\n- 開発環境/技術スタック\n言語: C/C++ (14/17), python\nミドルウェア、フレームワーク: CUDA / Eigen / OpenCV / TensorRT / ONNX\nOS: ubuntu\nその他: Slack / Git / GitHub Copilot / JIRA / Confluence\nRequirements\nトラックを用いたレベル4自動運転システムの開発を担います。自動運転は周囲の環境を高精度に認識し安全かつ快適な走行経路に車両を導くというタスクです。様々な技術的チャレンジがあり、機械学習、数理最適化、シミュレーション、組み込みシステムなど幅広い分野で人材を募集しています。\nPerception チームでは現在 Camera・LiDAR・Radar を用いたマルチモーダル3次元物体検出器を開発しており、開発したモデルは既に実車両にデプロイされ、公道走行に用いられております。T2ではデータ収集、アノテーションパイプライン、モデル開発、デプロイまで全て内製で開発しており、機械学習インフラにも投資がされております。\n本チームではこの3次元物体検出器にトラッキング・Predictionおよび周辺環境認識含めた機能の開発を担っています。このポジションでは、特に車載のエッジデバイス上でこれらの機能を実現する高品質・高効率なソフトウェアコンポーネントの設計・開発・評価に携わっていただきます。\n- 開発環境/技術スタック\n言語: C/C++ (14/17), python\nミドルウェア、フレームワーク: CUDA / Eigen / OpenCV / TensorRT / ONNX\nOS: ubuntu\nその他: Slack / Git / GitHub Copilot / JIRA / Confluence\nPreferred Experiences\n- コンピュータビジョン、ロボティクス関連分野における修士または博士号\n- 2D/3D object detection, monocular/multi-view depth estimation, BEV perception などの分野に関する専門知識と実装経験\n- LiDAR/radar/camera などのセンサーに関する専門知識\n- End-to-End 自動運転に関する専門知識\n- シミュレータを利用した性能検証経験\n- ROSなどのモジュールベースのフレームワークを用いたアプリケーション開発の経験\nWe are looking for\nWorking Conditions\nSalary\n※スキル、経験等による\n会社はテレワーク勤務も認め、詳細は別途定めるテレワーク規程による。\nLocation\n100-0011 東京都千代田区内幸町2-2-3 日比谷国際ビル1F\nJob Type\n業務委託\nWork hours\n稼働時間96時間 ~ 160時間（週24 ~ 40時間）を想定\n※応相談\nProbation 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