{"id":492256,"url":"https://alion.io/job/v-nova-integration-engineer-ai-pipelines","title":"Integration Engineer - AI Pipelines","company":{"id":15584,"name":"V-Nova","domain":"v-nova.com","url":"https://alion.io/company/v-nova","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"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":"Computer Vision","optional":false},{"name":"Embeddings","optional":false},{"name":"FFmpeg","optional":false},{"name":"GStreamer","optional":false},{"name":"Multimodal AI","optional":false},{"name":"NVIDIA NeMo","optional":false},{"name":"Python","optional":false},{"name":"Structured Outputs","optional":false},{"name":"AWS","optional":true},{"name":"C","optional":true},{"name":"CUDA","optional":true},{"name":"Docker","optional":true},{"name":"Function Calling","optional":true},{"name":"LLM","optional":true},{"name":"PyTorch","optional":true},{"name":"RAG","optional":true},{"name":"TensorRT","optional":true},{"name":"Triton Inference Server","optional":true},{"name":"VLM","optional":true}],"status":"live","first_seen_at":"2026-09-07T01:49:57Z","employer_posted_date":"2026-09-19","last_verified_at":"2026-10-26T08:10:13Z","board_verified":true,"closed_at":null,"days_open":49,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":49},"description":"Overview\nJoining V-Nova's Integration Team as a Software Engineer will give you the opportunity to work at the intersection of video engineering and artificial intelligence. You will help integrate V-Nova's video technologies multimodal workflows using Python to turn new ideas into practical, reliable systems.\nThe work will span offline video curation and large-scale dataset preparation through to real-time and cloud-based video inference. This will include building workflows, integrating codecs with AI and media frameworks, and exploring how LCEVC and VC-6 can reduce the amount of video data, decoding and processing required by AI applications.\nThe Integration Team's day-to-day work is dynamic. You will collaborate with codec engineers, AI specialists and external engineering teams, investigating unfamiliar systems and developing solutions that make V-Nova technology straightforward to evaluate and adopt. You are proactive, curious and comfortable contributing to wide-ranging technical discussions.\nResponsibilities\nDevelop and maintain production-quality Python integrations, tools and sample applications for V-Nova's LCEVC and VC-6 technologies within AI video workflows.\nIntegrate codec SDKs into video curation, data preparation and inference pipelines, including workflows using technologies such as NVIDIA NeMo Curator, with either native integrations or via frameworks such as FFmpeg and GStreamer.\nBuild and maintain video processing pipelines covering ingest, frame and clip extraction, transcoding, timestamps, keyframes, metadata and audio/video synchronisation.\nConnect video processing stages to computer-vision and multimodal AI models for tasks such as classification, detection, captioning, embeddings, retrieval and structured output generation.\nPrototype and benchmark codec-aware inference workflows, including the selective use of resolutions or regions of interest, and evaluate their impact on accuracy, latency, throughput, scalability and cost.\nCreate automated tests, performance measurements and clear technical documentation that help colleagues, customers and partners reproduce and evaluate integrations.\nCollaborate with colleagues and external engineering teams to scope work, communicate progress and deliver integrations to production.\nQualifications\nCommercial software development experience using Python, including writing maintainable, tested and documented code.\nPractical video engineering knowledge and a basic understanding of how video streams work, including codecs and containers, frame extraction, timestamps, keyframes, audio/video synchronisation, transcoding and streaming fundamentals.\nGood problem-solving skills and confidence working across unfamiliar codebases, third-party libraries and APIs.\nClear written and verbal communication, including concise progress updates and technical documentation.\nA degree in Computer Science, Engineering or a related discipline, or equivalent practical experience.\nDesirable Experience: \nExperience with virtualisation and containerisation technologies, including Docker, and an understanding of building and managing portable, scalable environments.\nExperience working with AWS or similar services and deploying, managing or supporting applications in cloud-based environments.\nExperience with video curation or data preparation frameworks, or with building scalable batch and streaming data pipelines.\nExperience with multimodal AI, including LLM or VLM APIs, image and video understanding, embeddings, structured outputs, tool or function calling, and retrieval-augmented generation.\nExperience deploying and optimising AI inference workloads, with an understanding of performance considerations such as latency, throughput, scalability and cost.\nDirect development experience with FFmpeg or GStreamer.\nExperience with GPU-accelerated video or AI technologies such as CUDA, 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