We are looking for a Senior Machine Learning Engineer to join our growing team and contribute to the development of cutting-edge computer vision products.
Our mission:
We deliver asymmetric advantages to our #adtech customers through vast domain expertise, simplicity, and #stellar level of service. We continue to challenge ourselves and grow as technologists, professionals, and, most importantly, as human beings who work side by side, day after day and year after year. And we don’t plan to stop anytime soon.
We put in the work, and we love it. Some days, we may fail, but only to try harder the next day. We work through our losses and celebrate our wins as one team.
Project
The platform specializes in media content analysis and delivers insights through advanced AI-driven content recognition technologies. The core objective is to continuously design, develop, and refine state-of-the-art computer vision models, such as object detection, image segmentation, classification, and facial recognition. These models are seamlessly integrated into the platform to enhance its capabilities.
Responsibilities
- Automate model training, evaluation, and deployment processes in development environments
- Build and maintain CI/CD pipelines specifically for model training and evaluation
- Ensure proper documentation for all tools, CI/CD pipelines, containers, and reusable code to maintain clarity and ease of use for future team members
- Document best practices and guidelines for integrating new models into the workflow
- Support continuous model retraining and monitoring efforts in collaboration with data scientists
- Extend and maintain available containers that are compatible with different stages of deployment (training, testing, etc.)
- Work closely with the software team responsible for putting model artifacts into the production pipeline, ensuring a smooth handoff of model outputs
- Maintain and continuously refactor reusable training/evaluation code, ensuring modularity and scalability
- Design and implement tools to support ML workflows, such as monitoring tools or visualization aids
Requirements
- 5+ years of experience in machine learning engineering
- Proven experience in building, maintaining, and automating CI/CD pipelines for machine learning projects
- Experience with model deployment and monitoring using AWS services
- Familiarity with cloud-based machine learning workflows and infrastructure
- Strong proficiency in Python, Bash, and Shell scripting for automation
- Proficiency in frameworks like TensorFlow, PyTorch, and Scikit-learn for model training and evaluation
- Hands-on experience with AWS services: Amazon S3, Amazon SageMaker, AWS Lambda, Amazon ECS/EKS
- Experience with Docker for the containerization of ML workloads
- Advanced level of English
Would be a plus:
- Knowledge of AWS Step Functions for orchestrating serverless workflows
- Familiarity with Terraform for managing AWS infrastructure as code
- Experience with distributed training
