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.