Job
Description
Role Summary The Senior Backend Engineer (Python & Node.js) is responsible for leading the design, implementation, and optimization of scalable machine learning infrastructure. This role ensures that AI/ML models are efficiently deployed, managed, and monitored in production environments while providing mentorship and technical leadership to junior engineers. You can apply using the link below. https://jobs.lever.co/welocalize/284fe16c-a7e3-4f88-bfc9-ba01fa3fcbc4 Key Responsibilities: Architectural Leadership: Lead the design and development of scalable, secure, and efficient AI/ML platform architecture, ensuring robust and reliable infrastructure. Automation & Deployment: Develop and implement advanced automation pipelines for model deployment, monitoring, and rollback, enhancing operational efficiency. Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists and product managers, to define platform requirements and support seamless model integration. Performance Optimization: Drive performance tuning, load balancing, and cost optimization strategies to ensure the platform's efficiency and scalability. Mentorship & Leadership: Mentor junior platform engineers, providing technical guidance and fostering a culture of best practices and continuous learning. Incident Management: Conduct post-mortems and root cause analysis for system failures and performance issues, implementing corrective actions to prevent recurrence. Qualifications Educational Background: Bachelors or Masters degree in Computer Science, Engineering, or a related field. Experience: 5+ years of experience in Python & Node.js engineering, with a proven track record in leading and executing complex projects. Technical Expertise: Expertise in cloud-based solutions (e.g., AWS, GCP, Azure), distributed systems, and microservices architecture. Proficiency in Terraform, Docker, and advanced automation tools. Proficiency in python and node.js. Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) and MLOps practices. Problem-Solving Skills: Excellent problem-solving skills with a proactive approach to identifying and addressing technical challenges. Leadership Skills: Strong leadership and mentoring skills, with the ability to guide and inspire engineering teams. Communication Skills: Exceptional communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.
