Join our dynamic team as a Machine Learning Engineer, where you'll play a pivotal role in designing and maintaining cutting-edge MLOps pipelines. Leverage your expertise to develop scalable solutions and integrate machine learning services seamlessly into applications.

Responsibilities

• Design and maintain end-to-end MLOps pipelines for data preparation, model training, and deployment.
• Create and manage FastAPI microservices for efficient model inference.
• Implement deployment strategies using GitOps and Argo CD on Azure Kubernetes Service.
• Develop a self-service MLOps platform to streamline model delivery processes.
• Ensure scalable and low-latency serving of machine learning models.
• Integrate telemetry for observability and establish service level objectives.
• Automate workflows for model retraining and safe deployment.
• Collaborate with cross-functional teams to integrate ML services into applications.
• Champion best practices for code quality and governance.

Skills

• Proficient in Python with experience in building services using FastAPI.
• Strong background in MLOps, including model packaging and API management.
• Experience with CI/CD pipelines for machine learning using GitHub Enterprise.
• Expertise in containerization and orchestration with Docker and Kubernetes.
• Familiarity with GitOps principles and deployment strategies.
• Solid understanding of RESTful API design and microservices architecture.
• Ability to work collaboratively with data scientists and engineers.

Preferred Skills

• Experience with ML lifecycle management tools like MLflow.
• Knowledge of Databricks and enterprise data environments.
• Cloud experience, particularly with Azure, and familiarity with GCP.
• Understanding of Agile methodologies and security best practices.

At Horizontal, we are committed to fostering a diverse and inclusive workplace where all individuals feel valued and respected. We believe that diversity drives innovation and creativity, and we welcome applicants from all backgrounds to join our team.