Middle Strong/Senior ML Data Engineer (#4403)

N-iX is a global software development service company that helps businesses across the globe create next-generation software products. Founded in 2002, we unite 2,400+ tech-savvy professionals across 40+ countries, working on impactful projects for industry leaders and Fortune 500 companies. Our expertise spans cloud, data, AI/ML, embedded software, IoT, and more, driving digital transformation across finance, manufacturing, telecom, healthcare, and other industries. Join N-iX and become part of a team where your ideas make a real impact.

N-iX is looking for a Data Engineer with ML Ops experience to deploy production ML models at significant scale. As part of the data licensing team, the successful candidate will work closely with data science and data engineering colleagues to apply state of the art models in production. Projects will vary from deploying models that provide new metadata for existing catalogue to developing novel techniques for asset retrieval. Given the magnitude of data and AI focus, this role presents unique and exciting opportunities that have an immediate revenue impact.

Our customer is a technology company that powers one of the world's largest two-sided marketplaces for high-quality photos, illustrations, videos and music used by individuals, businesses, marketing agencies and media organizations of all sizes. In this role, you will be working with highly motivated and talented data scientists and engineers who are primarily focused on developing next generation AI/ML systems that transform the way people find content they enjoy.

Responsibilities:

• Work with data scientists to design scalable ML pipelines that integrate into existing architecture. 
• Under the guidance of a principal engineer, take ownership of all ML ops and data engineering deliverables for an assigned project.
• Support the deployment of models into production environments (batch and/or real-time), including containerization, inference orchestration, and integration with relevant tools and services.
• Build internal tools (e.g., Streamlit apps) to showcase ML outputs.
• Display continual curiosity to drive innovation.
• Collaborate with platform teams to adopt and extend data ingestion framework
• Adopt and contribute to company wide best practices around coding quality, architecture, and code reviews.

Requirements

Essential:

• Experience designing and implementing large scale cost effective production workflows within AWS (lambda, kafka, kinesis, EKS, step functions)
• Experience working with data scientists to transition notebooks (Databricks,
  Sagemaker) into production code.
• Cost management
• Python
• DevOps (CloudWatch, CI/CD pipelines, IaC)
• Pipeline Orchestration, ideally Airflow.

Nice to have:

• MLFlow
• DBT
• Frontend Experience
• Spark / Pyspark