Our Client is a marketing and brand consultancy, with proprietary market research and advertising solutions grounded in the principles of behavioral science. The Company specializes in helping clients with their communication and innovation programs and works with many of the world’s largest buyers of advertising and market research. The Client offers a range of tools that embody the latest trends in research. Predictive Markets tool uses the “wisdom of the crowd” to identify winning concepts.
N-iX provides services to the client in the areas of software development, software quality control and quality assurance, technical support and consultancy professional services to the client’s end customers.
Requirements:
3+ years of development experience in the ML domain (build training and inference pipelines, manage model deployment) MLOps e.g. MLflow General Data Engineering Deep learning, hosting LLMs, multimodal LLM Experience with Azure (Azure Container Apps, Service Bus, Azure SQL), MLOps pipelines setup in Azure ML Expertise with Python, ML Stack (PyTorch, transformers, torchcodec, scikit-learn), DevOps (CI/CD, IaC), ML Monitoring setup required Experience with building and owning highly available, fault-tolerant backend systems using cloud storage services Experience building software for database administration or experience with devops for databases is a plus. Extensive experience with model serving, deployment, compression, performance optimization, end to end machine learning lifecycle Advanced English written and verbal communication skills (C1/C2) Master's degree in Computer Science, or a related fieldNice to have:
Experience with AWS Experience in other programming languages (like .Net) Experience in setting up, configuring and maintaining CI/CD process Familiarity with building dashboards and visualizations using toolsResponsibilities:
Implement best practices for version control, testing, and monitoring of machine learning models and infrastructure Identify and resolve performance bottlenecks and other issues that impact the reliability and efficiency of machine learning systems Ensure the security and compliance of ML systems with internal and external standards and regulations Continuously research and evaluate new tools and technologies to improve the efficiency and effectiveness of ML operationsWe offer*:
Flexible working format - remote, office-based or flexible A competitive salary and good compensation package Personalized career growth Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more) Active tech communities with regular knowledge sharing Education reimbursement Memorable anniversary presents Corporate events and team buildings Other location-specific benefits*not applicable for freelancers