Senior Software Engineer, AI/ML Platform

Job Description

Senior Software Engineer, AI/ML Platform | Not Specified

The Tone:
This is a full-time role at Not Specified, with hybrid/remote options available. The company is a cutting-edge technology company revolutionizing a specific industry sector through AI-driven solutions. Their mission is to empower businesses with intelligent decision-making and enhance user experiences through personalized services. This role is pivotal for designing, building, and maintaining the core infrastructure and tools that allow data scientists and machine learning engineers to rapidly develop, deploy, and scale AI models, impacting millions of users and driving significant business value.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: [City, State, Country] (Hybrid/Remote Options Available)

• Team: AI/ML Platform team
• Mission: Design, build, and maintain the core infrastructure and tools that enable rapid development, deployment, and scaling of AI models.
• Tech Stack: Python, TensorFlow, PyTorch, scikit-learn, Docker, Kubernetes, Spark, Kafka, Jenkins, GitLab CI, GitHub Actions, AWS, Azure, GCP

What You’ll Actually Do
• Platform Development: Design and develop robust, scalable, and efficient MLOps platforms and tools for model training, versioning, deployment, monitoring, and lifecycle management.
• Stakeholder Collaboration: Collaborate with data scientists and ML engineers to understand their needs and translate them into technical solutions.
• Data Infrastructure: Build and optimize data pipelines and feature stores to provide high-quality, reliable data for ML models.
• Automation: Implement and maintain CI/CD pipelines specifically tailored for machine learning workflows.
• System Reliability: Ensure the reliability, performance, security, and cost-efficiency of the AI/ML infrastructure, often leveraging cloud-native services.

The Must-Haves
• Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. Career level: Senior.
• Experience: 5+ years of professional experience in software development, with at least 2 years focused on building and scaling ML platforms, MLOps, or data infrastructure.
• Skills: Strong proficiency in Python and common ML libraries, solid understanding of distributed systems and microservices architecture, experience with cloud computing principles (AWS, Azure, or GCP), containerization technologies (Docker, Kubernetes), and CI/CD tools.
• Bonus: Experience with MLOps tools like MLflow or Kubeflow, familiarity with infrastructure-as-code (Terraform), and experience with real-time data streaming.