Software Engineer II (AI | Up to 40LPA)

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗷𝗼𝗯This role is for one of our client companies — a VC-backed Construction Technology (ConTech) startup that has raised $49.7M USD in funding.𝗦𝗮𝗹𝗮𝗿𝘆: Up to 40LPAApply once and, if selected, get access to up to 20 remote and onsite interview opportunities.🚀 𝗪𝗵𝗮𝘁 𝗪𝗲'𝗿𝗲 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴CodeRound AI matches the top 5% tech talent with the fastest-growing, VC-funded AI startups across Silicon Valley and India.Top-tier product startups across the US, UK, EU, UAE, and India have hired top engineers through CodeRound.🚀 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 - 𝗜𝗜 (𝗔𝗜) (3+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲)As an SDE-II AI Engineer, you will sit at the intersection of our AI Research and Engineering teams, owning the path that takes computer vision, NLP, and multi-modal models from research prototypes to reliable, scalable production systems.🧩 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼Own the end-to-end MLOps lifecycle, from model packaging and CI/CD to deployment, monitoring, and rollback for computer vision, NLP, and multi-modal models.Design and maintain scalable training and inference pipelines for large datasets and models, optimizing for cost, latency, and throughput.Build and manage containerized deployment infrastructure (Docker, Kubernetes) for hosted deep learning and geoprocessing services.Set up and maintain experiment tracking, model registry, and versioning systems to ensure reproducibility across the research-to-production lifecycle.Implement model monitoring and observability — drift detection, performance degradation alerts, logging, and dashboards, for models running in production.Apply model optimization techniques (quantization, pruning, knowledge distillation) to improve inference efficiency in production.Collaborate with Research Engineers, Backend Engineers, and Product teams to translate research ideas into deployable, production-ready services.Develop and maintain infrastructure-as-code, monitoring, and logging for all deployed ML/AI software.✅ 𝗬𝗼𝘂'𝗿𝗲 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁 𝗜𝗳 𝗬𝗼𝘂3+ years of experience in MLOps, ML infrastructure, or applied AI/ML engineering, with exposure to Computer Vision or NLP systems.Hands-on experience with workflow orchestration frameworks (preferably Temporal) for building reliable, fault-tolerant, long-running distributed workflows.Strong proficiency in Python and hands-on experience with ML frameworks such as PyTorch, TensorFlow, OpenCV, or HuggingFace Transformers.Hands-on experience with Docker, Kubernetes, and containerized ML deployment pipelines in production environments.Experience building and maintaining CI/CD pipelines for ML systems (e.g., Jenkins, GitHub Actions, GitLab CI).Working knowledge of experiment tracking and model registry tools (e.g., MLflow, Weights & Biases, DVC).✨ 𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?Own meaningful product decisions from day one at a funded startupWork with a sharp team shipping fast in a high-growth environmentAccelerate your career with outsized responsibility and visibilityBuild something that scales — not slide decks