Machine Learning Engineer

Introduction DeCentralCode:

DeCentralCode is a technology company that applies modern solutions to address current challenges. With locations in Rotterdam, Netherlands and Salem, India, we operate on a global scale. Our expertise lies in cutting-edge technologies such as machine learning/artificial intelligence, distributed ledger technology, blockchain, Internet of Things, cloud-native, serverless architecture, and cybersecurity. We collaborate with knowledge institutions, governments, and businesses to co-create and validate solutions for various domains including supply chain and energy transition, among others. As an early-stage partner, we offer the opportunity to work with the cutting-edge technologies from scratch.

Location:

Salem, Tamil Nadu, India.

We are looking for:

As a Machine Learning Engineer, you will be responsible for designing, developing, and implementing machine learning algorithms and models to solve complex business problems and enhance our products and services. You will collaborate closely with cross-functional teams, including data scientists, software engineers, and product managers, to drive the development and deployment of machine learning solutions. Ability to identify and solve complex problems using machine learning techniques, with a focus on delivering actionable insights and tangible business value. Implement best practices for testing and validation of machine learning models, ensuring robustness, reliability, and reproducibility of results. Effectively communicate technical concepts and insights to non-technical stakeholders, and present findings and recommendations in a clear and concise manner.

Responsibilities:

Understanding the functional aspects of the client's requirement. Ability to work in an Agile environment at scale. Ability to work independently and as part of a team. Efficient Task Execution and adherence to schedules, timelines. Raise clarifications, issues, concerns regarding work output to the lead on time. Provide periodic task level updates as required. Ensure appropriate classification and prioritization of tasks. Comply with defined process during task execution. Assisting in creating documentations about client specific applications project

specific processes and workflows. Adhere to company policies and procedures. Participation In Calls, Status Reporting Participating in daily stand-up calls and weekly calls. Attend any Knowledge Transition sessions conducted within the project to gain proficiency in project level knowledge. Understanding details of the quality processes and practices followed in the project from different sources. Completing the domain, technical, project relation training and certifications.

Necessary Skills:

Must Have:

4+ years of hands-on experience in deep learning and computer vision. Strong proficiency in PyTorch and deep learning workflows. Solid experience with CNN architectures such as ResNet, EfficientNet, or equivalent. Good understanding of ordinal classification and multi-output learning techniques. Expertise in data pipeline development, including preprocessing, augmentation, and validation. Strong knowledge of statistical analysis and model evaluation methodologies. Proficiency in Python and its data science ecosystem: NumPy, pandas, scikit-learn, matplotlib/seaborn. Experience with Git version control and clean, maintainable coding practices.

Good to Have:

Experience working with medical imaging or healthcare AI solutions. Knowledge of mobile and edge model optimization techniques (ONNX, TensorRT, CoreML). Familiarity with domain adaptation and transfer learning methods. Exposure to Bayesian deep learning and uncertainty quantification approaches. Experience using data annotation tools and managing annotation workflows.