Senior Machine Learning Engineer

Top 3 Reasons To Join Us Work closely with international team members Your work will be critical to shaping the solution Challenging projects with flexible working hours The Job We are seeking a Senior Machine Learning Engineer to join our core team. This role spans the entire AI lifecycle—from architectural design and model building to production-grade deployment and MLOps. You will own the quality, performance, and scalability of our machine learning systems, focusing specifically on scaling AI products to handle high-volume, enterprise-level workloads. Key Responsibilities AI Architecture & Scalability: Lead the design and development of high-performance ML systems capable of scaling across large-scale enterprise environments. Production MLOps: Design, automate, and maintain robust end-to-end MLOps pipelines (CI/CD for ML) using Docker, Kubernetes, or cloud-native tools to ensure reliable model deployment and automated scaling. Monitoring & Optimization: Implement advanced monitoring (e.g., tracking data drift, latency, and model performance) using tools like Prometheus/Grafana to ensure continuous uptime and resource optimization. Research & Innovation: Evaluate and apply the latest deep learning algorithms and LLM techniques to solve complex business problems. Technical Leadership: Mentor junior engineers, conduct strict code reviews, and help shape the company's long-term AI technology roadmap. Cross-functional Collaboration: Work closely with Product Managers and Software Engineers to translate product requirements into scalable technical architectures. Your Skills and Experience Experience: 5 to 10+ years of hands-on experience as an ML Engineer, with a proven track record of architecting and deploying production-grade AI solutions for large-scale systems . Cloud Platforms: Strong experience implementing enterprise AI/ML solutions on Azure and/or AWS . Core Tech Stack: Deep proficiency in Python (NumPy, Pandas, Scikit-learn) and major deep learning frameworks ( PyTorch or TensorFlow ). MLOps Mastery: Practical experience with MLOps frameworks (MLflow, Kubeflow, CI/CD pipelines) and containerized workflows (Docker, Kubernetes). Data & Distributed Systems: Strong SQL skills and experience handling big data technologies (e.g., Apache Spark, Kafka) to manage massive data pipelines. System Design: Solid understanding of distributed system architecture, database optimization, and clean coding principles. You will be successful if you have: English Fluency: Excellent written and verbal English communication skills for working in an international environment. Communication: Ability to articulate complex AI/ML architectural concepts clearly to both technical and non-technical stakeholders. Leadership: Strong mentoring skills with a passion for driving technical excellence across the engineering team. Execution: Highly organized, detail-oriented, and able to work independently to drive tight project deadlines. Why You'll Love Working Here Work remotely (full-time remotely or at co-working spaces if needed) with a competitive salary; Opportunity to lead and empower a talented team; Collaborative and supportive work environment with a focus on personal and professional growth; Continuous learning and development opportunities to stay ahead of the curve; Chance to make a significant impact on the company's success and shape the future of our products. If this sounds like a great role and an ideal work environment, we’d love to hear from you!