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 a company with an unspecified location. The company is seeking a Senior Software Engineer to join its AI/ML Platform team. This team builds the foundational infrastructure and tools that enable data scientists and machine learning engineers to create, deploy, and monitor advanced AI models, directly contributing to product innovation and impacting millions of users.

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

• Team: AI/ML Platform team, providing foundational infrastructure for intelligent features.
• Mission: Design, develop, and maintain scalable and robust infrastructure and tools for building, deploying, and monitoring AI models.
• Tech Stack: Python, Java, Go, Scala, AWS, Azure, GCP, Docker, Kubernetes, Spark, Flink, Kafka, SQL, NoSQL, TensorFlow, PyTorch, Scikit-learn, Prometheus, Grafana, ELK Stack

What You’ll Actually Do
• Platform Design: Design and implement highly scalable, reliable, and performant microservices for the AI/ML platform.
• Data Engineering: Develop and optimize data pipelines and feature stores to ensure efficient access and processing of large datasets for model training and inference.
• MLOps Streamlining: Build tools and frameworks to streamline the MLOps lifecycle, including model versioning, experimentation tracking, CI/CD for ML, and model deployment.
• Cross-functional Collaboration: Collaborate closely with data scientists, ML engineers, and other engineering teams to understand their needs and translate them into robust platform features.
• Architectural Guidance: Contribute to architectural discussions and decisions, promoting best practices in software engineering and MLOps.

The Must-Haves
• Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, with a significant focus on backend systems, platform engineering, or data infrastructure.
• Experience: 5+ years of professional software development experience. Extensive experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Skills: Strong proficiency in programming languages such as Python, Java, Go, or Scala. Solid understanding of distributed systems, microservices architecture, and API design principles. Experience with data processing technologies (e.g., Spark, Flink, Kafka) and various database systems (SQL/NoSQL). Familiarity with machine learning concepts and MLOps principles.
• Bonus: Experience building and maintaining machine learning platforms or MLOps tools from scratch. Familiarity with popular ML frameworks like TensorFlow, PyTorch, or Scikit-learn. Knowledge of stream processing and real-time analytics.