Senior Software Engineer, AI/ML Platform

Job Description

Senior Software Engineer, AI/ML Platform | InnovateTech Solutions

The Tone:
This is a Senior Software Engineer role at InnovateTech Solutions. The company is a technology leader in AI and data innovation, building intelligent solutions across various industries. This role is crucial for designing and developing the core platform that powers the company’s next generation of AI-driven products and services, directly impacting customers and the success of AI initiatives. The platform enables data scientists and machine learning engineers to rapidly develop, deploy, and monitor models.

The TL;DR
• Role: Full Time
• Team: AI/ML Platform
• Mission: This person builds and enhances the core infrastructure supporting the company’s entire machine learning lifecycle.
• Tech Stack: Python, Go, Java, Scala, AWS, GCP, Azure, Docker, Kubernetes, SQL, NoSQL, object storage, Spark, Flink, Kafka, MLflow, Kubeflow, Sagemaker, TFX, HDFS

What You’ll Actually Do
• Design: Lead the design and architecture of scalable, reliable, and high-performance components for the AI/ML platform, ensuring best practices in software engineering and system design.
• Develop: Implement core platform services for model lifecycle management, including versioning, deployment pipelines (CI/CD), serving infrastructure, and monitoring tools.
• Tooling: Create robust APIs, SDKs, and internal tools that streamline workflows for data scientists and ML engineers, enhancing their productivity and accelerating model development.
• Optimize: Identify and resolve performance bottlenecks within the platform, optimizing for latency, throughput, and resource utilization.
• Collaborate: Work closely with data scientists, ML engineers, product managers, and other engineering teams to understand requirements, gather feedback, and deliver impactful solutions.

The Must-Haves
• Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, combined with experience building scalable backend systems, distributed systems, or platform engineering.
• Experience: Requires 5+ years of professional software development experience, with a significant portion focused on building scalable backend systems or platform engineering. This includes strong experience with cloud computing platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration (Kubernetes).
• Skills: Expert-level proficiency in at least one modern programming language such as Python, Go, Java, or Scala. Solid understanding and practical experience with data storage (SQL, NoSQL, object storage) and data processing technologies (Spark, Flink, Kafka) is essential. Demonstrated ability to design, build, and maintain complex, fault-tolerant, and highly available systems, along with excellent problem-solving, analytical, and debugging skills.
• Bonus: Experience with MLOps principles and tools (e.g., MLflow, Kubeflow, Sagemaker, TFX) is preferred, alongside a basic understanding of machine learning concepts, algorithms, and workflows. Familiarity with distributed file systems (e.g., HDFS) and big data processing frameworks, plus contributions to open-source projects relevant to AI/ML or platform engineering, are a plus.