Sr Software Development Engineer - ML Ops

Everseen
: A leader in vision AI solutions for the world’s leading retailers.

• Teaching and Sharing Culture:
  • Share skills, knowledge, and expertise with members of the data engineering team.
  • Foster a culture of collaboration and continuous learning by organizing training sessions, workshops, and knowledge-sharing sessions.
• Design and Development:
  • Collaborate 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:
  • Create, maintain, and run unit tests for new and existing applications and services.
  • Aim to deliver defect-free and well-tested solutions.
• Data Analysis:
  • Analyze and collect data from various sources such as log files, application stack traces, and thread dumps.
  • Utilize 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):
  • Create and maintain CI/CD integration using various tools.
  • Automate the build, test, and deployment processes to ensure efficiency and reliability.
• Integration of Third-Party Solutions:
  • Research and propose third-party software solutions to optimize system performance.
  • Expand product capabilities by integrating compatible third-party solutions.
  • Monitor, update and tracking of third-party solutions  compatibility with Everseen stack according to internal development guidelines
• Monitoring and Troubleshooting:
  • Monitor production logs to identify and troubleshoot issues promptly.
  • Ensure 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.

• 5+ years of work experience in a relevant role and global SaaS company
• Bachelors degree or equivalent focusing on the computer science field is preferred
• Excellent communication and cross-functional collaboration skills.
• Comfort working in ambiguous and fast-evolving environments.

• Expert knowledge of Python
• Experience with CI/CD tools (e.g., Git Lab, Jenkins). Hands-on experience with Kubernetes, Docker, and cloud services.
• Understanding of ML training pipelines, data lifecycle, and model serving concepts
• Familiarity 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., Tensor Flow, PyTorch)
• GPU orchestration (e.g., NVIDIA GPU Operator, MIG)
• Infrastructure as Code (e.g., Terraform).
• Data engineering tools (e.g., Snowflake, Databricks, Big Query, 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 Elastic Search 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 IaaS, PaaS, and SaaS.
• Broa…