Everseen: A leader in vision AI solutions for the world’s leading retailers.
What you’ll do
Teaching and Sharing Culture
Shares skills, knowledge, and expertise with members of the data engineering team.Fosters a culture of collaboration and continuous learning by organizing training sessions, workshops, and knowledge-sharing sessions.
Design and Development
Collaborates and drive progress with cross-functional teams to design and develop new features and functionalities. Ensure that the developed solutions meet project objectives and enhance user experience.
Influence and Decision-Making
Have influence over the technology stack and internal technical improvements, contributing to strategic decision-making.
Coding
Based on requirements and a longer-term product and feature strategy, design and implement reusable, testable, efficient, and elegant code.Ensure adherence to coding standards and best practices.
Testing
Creates, maintains, and runs unit tests for new and existing applications and services.Aims to deliver defect-free and well-tested solutions.
Data Analysis
Analyzes and collect data from various sources such as log files, application stack traces, and thread dumps.Utilizes data analysis to identify trends, patterns, and potential areas for improvement. Based on this, begin to implement changes.Continuous Integration and Continuous Deployment (CI/CD):Creates and maintains CI/CD integration using various tools.Automates the build, test, and deployment processes to ensure efficiency and reliability.
Integration of Third-Party Solutions
Researches and proposes third-party software solutions to optimize system performance.Expands product capabilities by integrating compatible third-party solutions.Monitors update and tracking of third-party solutions' compatibility with Everseen stack according to internal development guidelines.
Monitoring and Troubleshooting
Monitors production logs to identify and troubleshoot issues promptly.Ensures seamless operation and timely resolution of any anomalies to maintain system reliability.
Documentation
Responsible for creating, reviewing, and maintaining high-quality technical documentation to ensure clarity, consistency, and knowledge sharing within the development team.
Profile and skills:
4-5 years of work experience in a relevant role and global SaaS companyBachelors degree or equivalent focusing on the computer science field is preferredExcellent communication and cross-functional collaboration skills.Comfort working in ambiguous and fast-evolving environments.
Technical Skills: Expert knowledge of PythonExperience with CI/CD tools (e.g., GitLab, Jenkins). Hands-on experience with Kubernetes, Docker, and cloud services.Understanding of ML training pipelines, data lifecycle, and model serving conceptsFamiliarity with workflow orchestration tools (e.g., Airflow, Kubeflow, Ray, Vertex AI, Azure ML).A demonstrated understanding of the ML lifecycle, model versioning, and monitoring.
Experience with:ML frameworks (e.g., TensorFlow, PyTorch)GPU orchestration (e.g., NVIDIA GPU Operator, MIG),Infrastructure as Code (e.g., Terraform).Data engineering tools (e.g., Snowflake, Databricks, BigQuery, Airbyte, Kafka)Familiarity with feature stores and model registries. Exposure to large-scale distributed systems and performance optimisation. Ability to work with Linux systems, including troubleshooting skills such as log investigations, performance testing, and connectivity investigation.Possesses a deep understanding of technical concepts and terminology relevant to Everseen's products and services. Expert knowledge of advanced concepts like microservices and distributed systems, indicating an understanding of modern software development architectures. In-depth knowledge of Azure Kubernetes Services for container orchestration, Azure Blob Storage for data storage, and ElasticSearch for search and analytics. Ability to leverage cloud computing technologies and services for testing and validation purposes. In-depth knowledge of cloud security, scalability, and performance optimization principles. Excellent understanding of cloud computing technologies and services, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Broad understanding of the software engineering and architecture space, including knowledge of various programming languages, frameworks, techniques, and industry trends in AI. 
