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.