Middle ML Data Engineer

N-iX, a global software development company with 2,400+ professionals, seeks a Middle ML Data Engineer. The role involves designing scalable ML pipelines, taking ownership of MLOps and data engineering deliverables, supporting model deployment into production environments (batch and/or real-time), building internal tools to showcase ML outputs, and collaborating with platform teams. The ideal candidate will drive innovation and contribute to company-wide best practices in coding quality and architecture.

Must Have

• Work with data scientists to design scalable ML pipelines that integrate into existing architecture.
• 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.
• 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.
• Proficiency in Python.
• Experience with DevOps (CloudWatch, CI/CD pipelines, IaC).
• Experience with Pipeline Orchestration, ideally Airflow.

Good to Have

• MLFlow
• DBT
• Frontend Experience
• Spark / Pyspark

Perks & Benefits

• 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

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 MLOps experience to join our team.

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

We 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