AI and Data Engineer

We re looking for a skilled AI and Data Engineer to join our team. You ll be at the forefront of designing, building, and maintaining the infrastructure that powers our data-driven products and machine learning models. This role requires a strong blend of data engineering expertise, a deep understanding of MLOps principles, and the ability to work with large-scale datasets. You will be responsible for creating robust data pipelines, managing our data platforms, and collaborating with data scientists and software engineers to bring AI solutions to life.

Requirements

• MSc or PhD in Computer Science, Data Science, AI/ML, Biostatistics, or a related quantitative field
• 2-5 years of experience developing technical solutions for automation or AI
• Strong programming skills in Python and experience with Big Data applications
• Hands-on experience with AWS, Azure, or GCP, including their data and ML services
• Solid understanding of data lifecycle management, data architecture, and governance
• Experience with CI/CD pipelines and MLOps tools
• Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders

Will be a Plus

• Experience with Docker and Kubernetes for containerization and orchestration
• Knowledge of real-time data processing technologies like Apache Kafka or Amazon Kinesis
• Familiarity with data observability, testing, and automation frameworks

Responsibilities

• Design, build, and maintain scalable data pipelines using tools like Apache Spark, Airflow, and AWS Glue
• Manage and optimize cloud-based data platforms, including data lakes (S3) and data warehouses (Redshift, BigQuery)
• Solve complex data integration challenges using optimal ETL patterns, sourcing from structured and unstructured data
• Develop and implement MLOps frameworks to automate deployment, monitoring, and lifecycle management of ML models
• Transition experimental models into production-ready code and integrate them into applications with software engineering teams
• Apply best practices in CI/CD, using tools like Jenkins, GitLab CI, and MLflow or Kubeflow
• Build interactive dashboards and data products to support analytics and decision-making
• Collaborate with product, QA, architecture, and engineering teams to deliver cleanly integrated data services
• Support teams with robust, well-documented data models and infrastructure
• Continuously monitor and improve the performance and cost-efficiency of data and AI infrastructure
• Drive innovation by evaluating open-source tools and emerging technologies, and recommending solutions
• Influence product and cross-functional teams to identify data opportunities that drive measurable impact

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.