ML Engineer (Upto 25 LPA)

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗷𝗼𝗯
This role is for one of our client companies — a VC-backed Digital Document Infrastructure startup that has raised $6.5M USD in funding.
𝗦𝗮𝗹𝗮𝗿𝘆: Up to 25LPA
Apply once and, if selected, get access to up to 20 remote and onsite interview opportunities.
🚀 𝗪𝗵𝗮𝘁 𝗪𝗲'𝗿𝗲 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴
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.
🚀 𝗠𝗟 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 (3+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲)
We are seeking a Machine Learning Engineer with 3+ years of experience to design, deploy, and scale advanced NLP and Computer Vision models. If you excel at turning unstructured document data into production-ready AI solutions, we want to hear from you.
🧩 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼
Design, develop, and deploy ML models for document intelligence, content processing, and automated information extraction.
Build end-to-end ML pipelines for processing unstructured text, images, scanned documents, and PDFs.
Develop and improve NLP and CV solutions for document classification, entity extraction, semantic search, and document understanding.
Experiment with deep learning architectures, Transformers, and LLM-based approaches to solve real-world document processing challenges.
Convert research prototypes and experimental models into reliable, scalable, production-ready systems.
Evaluate model performance using appropriate metrics, statistical analysis, benchmarking, and error analysis.
Optimize model accuracy, inference speed, scalability, and resource utilization for production workloads.
Build and maintain REST APIs and integrate ML models into existing product workflows.
✅ 𝗬𝗼𝘂'𝗿𝗲 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁 𝗜𝗳 𝗬𝗼𝘂
3+ years of hands-on experience in Machine Learning Engineering, with a strong focus on Computer Vision, NLP, or document intelligence.
Strong proficiency in Python, with experience writing production-quality, maintainable code.
Practical experience building, training, evaluating, and deploying machine learning and deep learning models.
Strong understanding of deep learning architectures, including CNNs and Transformers, along with fundamental ML algorithms, mathematics, and statistics.
Experience with PyTorch and the Hugging Face Transformers ecosystem.
Hands-on experience with unstructured text and document data, including text classification, information extraction, document understanding, or semantic search.
✨ 𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?
Own the deployment of production ML systems that redefine document infrastructure.
Drive immediate product impact with $6.5M in Series A backing.
Accelerate your career in a high-growth, remote-first engineering culture.
Collaborate daily with a world-class, ambitious team of builders.

Work arrangement
Yes