Senior Machine Learning Engineer

Senior ML / Computer Vision Engineer Introduction DeCentralCode: DeCentralCode is a global technology company with operations in Rotterdam, NL and Salem, TN. Focused on delivering modern technology solutions for real-world challenges. Our expertise spans cutting-edge technologies including Machine Learning/Artificial Intelligence, Computer Vision, Distributed Ledger Technology, Blockchain, Internet of Things (IoT), Cloud-Native and Serverless Architecture, and Cybersecurity. We collaborate with knowledge institutions, governments, and businesses to co-create and validate innovative solutions across multiple domains such as healthcare, supply chain, and energy transition. As an early-stage technology partner, we provide opportunities to build scalable products from the ground up using advanced and emerging technologies. Location: Salem, Tamil Nadu, India. We are looking for: We are developing advanced AI-driven solutions using Computer Vision, Deep Learning, and scalable Machine Learning technologies. The team is focused on building high-performance, production-ready AI systems with strong emphasis on model accuracy, reproducibility, optimisation, and scalable deployment architectures. We are looking for a Senior ML / Computer Vision Engineer to lead the design, development, and optimisation of AI systems powering the products. This is a hands-on individual contributor role involving end-to-end ownership of machine learning workflows, including dataset strategy, evaluation protocols, model architecture design, experimentation, and deployment pipelines. The role reports directly to the CTO/CPO, who has a strong ML background and serves as a technical sparring partner while expecting the candidate to drive key ML and Computer Vision decisions independently. Responsibilities: Own and manage end-to-end ML and Computer Vision pipelines from data processing to deployment. Design, develop, and optimize scalable Deep Learning and AI models. Define evaluation protocols, model architectures, and technical strategies. Build reproducible MLOps workflows including experiment tracking and model versioning. Analyze model performance and improve accuracy, scalability, and inference efficiency. Collaborate with cross-functional teams to validate and enhance AI solutions. Mentor junior ML engineers and provide technical guidance. Work in an Agile environment with strong ownership of deliverables and timelines. Identify technical risks, raise blockers proactively, and ensure high-quality execution. Maintain technical documentation, engineering standards, and development best practices. Necessary Skills: Must Have: 5+ years of production experience in ML, Deep Learning, and Computer Vision. Strong expertise in Python, PyTorch, and modern AI/ML workflows. Hands-on experience with CNN architectures like ResNet, EfficientNet, or similar. Experience building and deploying production-grade Computer Vision systems. Strong knowledge of data pipelines, preprocessing, augmentation, and validation. Good understanding of statistical analysis, model evaluation, and optimization. Experience with ordinal classification and multi-output learning techniques. Self-driven experimentation and problem-solving mindset. Proficiency in NumPy, pandas, scikit-learn, and related Python ML libraries. Experience with Git, clean coding practices, and reproducible workflows. Familiarity with AI-assisted development tools and Agile delivery practices. Ability to build MVPs quickly and iterate scalable AI solutions efficiently. Good to Have: Experience in Medical Imaging, Healthcare AI, and Medical Image Analysis. Hands-on experience working with small-data ML environments and multi-annotator datasets. Knowledge of model optimization and on-device deployment using ONNX, TensorRT, or CoreML. Familiarity with transfer learning, domain adaptation, and uncertainty quantification techniques. Experience managing data annotation workflows and annotation tools. Working knowledge of regulated software standards such as IEC 62304 and MDR.