Machine Learning Engineer

Description:

We are looking for a mid-level MLE who is knowledgeable and passionate about machine learning, software engineering, and cloud infrastructure. You will be working in the MLOps team, whose primary responsibility is to enhance the efficiency of producing machine learning products and developing machine learning platform. The scope includes but is not limited to building an end-to-end machine learning platform and governing best practices for software engineering, including Cloud infra, MLOps principle.

In this role, you will:

• Build machine learning infrastructure that enables face-paced ML development, including notebook servers, training and deployment pipelines, metadata store, model antifactory, feature store, serving infrastructure, and monitoring system and feedback loop.
• Exercise MLOps best practices. Implement continuous-X automated pipelines, namely continuous integration (CI), continuous delivery (CD), and continuous training (CT).
• Maintain high SLAs. Ensure that the infrastructure is highly available, reliable, and scalable, and it always meets the service-level agreements (SLAs).
• Design and implement Software for serving AI Features, from backend to architecture to support ML workloads
• Make decisions with cost awareness in mind by optimizing design and workflow for machine learning infrastructure.

You will need to have:

• Strong problem-solving and software engineering skills
• Experience With GCP or other cloud providers, and utilizing managed services in architecture design
• Fundamental knowledge of data sciences and machine learning
• Working with SRE/Devops team to design and develop solutions emphasizing reliability, scalability and maintainability
• Experience writing infrastructure as code using tools like Terraform
• Proficiency in tools for building reliable systems like:
• VCS: Gitlab, Github
• CI/CD: Gitlab CI, Github Action, Jenkins, CircleCI
• Virtualization technology: VM, Docker, Kubernetes
• At least one of these programming languages: Python, C++, JavaScript
• Working in the Linux environment
• Experience or desire to work with scrum practices or agile processes
• English proficiency (professional level)

Nice to have:

• Experience pushing LLMs (or other generative AI) into production
• Experience with relational databases, NoSQL databases, data warehouses, and ETL frameworks is a plus.
• Experience QA testing process and Chaos Engineering