We are looking for an experienced Senior Machine Learning Engineer who will be responsible for developing and improving machine learning solutions for IoT products, including data analysis, model development, and deployment to production environments. This role requires strong expertise in machine learning algorithms, hands-on experience with training and optimizing models, and the ability to take ownership of technical decisions while working closely with a cross-functional team. Responsibilities: * Manage and maintain structured and unstructured data assets for ML workflows. * Design, implement, and optimize pipelines for training and deploying ML models. * Ensure model quality, performance, and monitoring in production environments. * Deploy and maintain models using cloud infrastructure (AWS). * Collaborate with cross-functional teams to deliver scalable ML solutions. * Continuously evaluate and refine model accuracy and efficiency. * Working with computer vision algorithms and ML models by using YOLO architecture. * Working with Edge AI and model optimisation.
Requirements: * 4+ years of experience in Machine Learning or Data Science roles. * Strong proficiency in Python and core data science libraries (e.g., Pandas, NumPy, etc.). * Experience with computer vision and object detection & classification algorithms must be had. * Experience with deep learning frameworks such as TensorFlow or PyTorch. * Familiarity with ML tools in production: MLflow, TensorFlow Serving, TorchServe. * Solid understanding and hands-on experience with Docker and containerized applications. * Experience deploying ML models on cloud platforms, especially AWS. * Strong background in data analysis, model evaluation, and optimization. * Ability to work independently and take ownership of end-to-end ML projects.
Our Benefits: * Professional growth: Individual development plan, mentorship, reimbursement for professional certifications and English lessons, access to professional courses in Corporate Learning Management System. * Community: Tech community and knowledge-sharing events, English speaking club, corporate library and book club, volunteering and charity initiatives. * Wellbeing: Medical insurance, regular medical check-ups, sport reimbursement, paid vacation and sick leave, mental health support, and events. * Work environment: Fully-equipped offices, top-notch equipment, flexible work format, activities both in-office and online, Y-bucks, and access to the Yalantis store.
Please note that feedback on the results of the CV review will be provided only in the event of a decision to consider your candidacy further. Otherwise, your data will be retained in the company’s CV database, and we will gladly contact you if a suitable vacancy becomes available. The consideration period is 7 working days.
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