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This role is for one of our client companies — a VC-backed Construction Technology (ConTech) startup that has raised $49.7M USD in funding.

??????: Up to 40LPA

Apply once and, if selected, get access to up to 20 remote and onsite interview opportunities. ? ???? ??'?? ????????

CodeRound 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. ? ???????? ???????? - ?? (??) (3+ ????? ?? ??????????)

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. ? ???? ???'?? ??

Own 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. ✅ ???'?? ? ????? ??? ?? ???

3+ 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). ✨ ??? ???? ???

Own meaningful product decisions from day one at a funded startup

Work with a sharp team shipping rapid in a high-growth environment

Accelerate your career with outsized responsibility and visibility

Build something that scales — not slide decks

📌 Software Engineer II (AI | Up to 40LPA) (India)
🏢 CodeRound AI
📍 India