Senior Software Engineer, AI Platform

Job Description

Senior Software Engineer, AI Platform | Not Specified

The Tone:
This is a full-time Senior Software Engineer role at a company focused on building core infrastructure for cutting-edge AI products and services. The position is critical for designing, developing, and maintaining scalable systems that enable data scientists and machine learning engineers to rapidly develop, deploy, and monitor AI models. This directly impacts millions of users by accelerating the speed, reliability, and efficiency with which AI models are brought to production and deliver value.

The TL;DR
• Role: Full Time
• Type: Full-time
• Location: Not Specified

• Team: AI Platform team
• Mission: This role focuses on evolving the AI infrastructure by working on critical components to bring AI models to production quickly and reliably.
• Tech Stack: Python, Java, Go, Scala, Kubernetes, Docker, AWS, GCP, Azure, Spark, Flink, Kafka, SQL, NoSQL, MLflow, Kubeflow, Sagemaker, TFX, TensorFlow, PyTorch

What You’ll Actually Do
• Design and Development: Lead the design, architecture, and implementation of scalable, reliable, and high-performance software for core AI platform components, including distributed training frameworks, inference engines, and data management systems.
• System Optimization: Identify and resolve performance bottlenecks, ensuring the efficient operation of the AI platform across various environments and workloads.
• Collaboration: Work closely with data scientists, machine learning engineers, and other engineering teams to understand their needs, gather requirements, and deliver solutions that accelerate their workflows.
• Code Quality and Best Practices: Champion best practices in software development, including code reviews, testing, documentation, and continuous integration/continuous deployment (CI/CD).
• Technical Leadership: Mentor junior engineers, contribute to technical strategy, and drive the adoption of new technologies and methodologies within the team.

The Must-Haves
• Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, with a significant focus on building scalable backend systems or infrastructure.
• Experience: 5+ years of professional experience in software development, with strong practical experience in distributed systems concepts, microservices architectures, and cloud-native development using major cloud providers (AWS, GCP, Azure).
• Skills: Expert-level proficiency in Python (highly preferred), Java, Go, or Scala; strong understanding of distributed systems and cloud platforms; hands-on experience with large-scale data processing technologies (Spark, Flink, Kafka) and various database systems (SQL and NoSQL); excellent analytical and problem-solving skills.
• Bonus: Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow, Sagemaker, TFX); basic understanding of machine learning concepts, algorithms, and common frameworks (e.g., TensorFlow, PyTorch); experience with performance tuning and optimization of large-scale systems; prior contributions to open-source projects, especially in the AI/ML or infrastructure domain.