{"@context":"https://schema.org/","@type":"JobPosting","title":"Senior Machine Learning Engineer","description":"## Top 3 reasons to join us\n\n

Work closely with international team members
Your work will be critical to shaping the solution
Challenging projects with flexible working hours

\n\n## Job description\n\n

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.

\n\n## Key Responsibilities\n\n

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.

\n\n## Your skills and experience\n\n

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.

\n\n## You will be successful if you have:\n\n

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.

\n\n## Why you'll love working here\n\n

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!

","datePosted":"2026-06-20","hiringOrganization":{"@type":"Organization"},"employmentType":"onsite"}