Senior Software Engineer – AI/ML Platform

Job Description

Senior Software Engineer – AI/ML Platform | InnovateX Tech

The Tone:
This is a full-time role at InnovateX Tech, a company dedicated to building intelligent systems that transform industries and improve lives through artificial intelligence. This position is vital for designing, developing, and maintaining the scalable, robust infrastructure and tools that empower data scientists and ML engineers to efficiently build, train, and deploy machine learning models. The role directly shapes the future of the company’s AI capabilities by working with cutting-edge technologies.

The TL;DR
• Role: Full Time
• Type: Full-time

• Team: AI/ML Platform team
• Mission: Design, develop, and maintain scalable, robust, and high-performance infrastructure and tools that empower data scientists and ML engineers to build, train, and deploy machine learning models efficiently.
• Tech Stack: Python, Go, Java, Scala, AWS, GCP, Azure, S3, EC2, Lambda, Sagemaker, GCP AI Platform, GKE, Azure ML, MLflow, Kubeflow, Airflow, Docker, Kubernetes

What You’ll Actually Do
• Design and optimize core components of the AI/ML platform, including data pipelines, model training frameworks, serving infrastructure, and monitoring systems.
• Develop tools and services that streamline the entire machine learning lifecycle from experimentation to production deployment, adhering to MLOps principles.
• Collaborate with data scientists, ML engineers, and product managers to understand their needs and translate them into platform features.
• Ensure the scalability, reliability, security, and cost-efficiency of the ML platform while operating on cloud infrastructure.
• Implement and enforce best practices for software engineering, including code reviews, automated testing, continuous integration/delivery (CI/CD), and documentation.

The Must-Haves
• Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• Experience: 5+ years of professional software development experience, with significant focus on building large-scale distributed systems or platform services.
• Skills: Strong proficiency in Python, Go, Java, or Scala; demonstrative experience with cloud platforms (AWS, GCP, or Azure) and their services; solid understanding of data structures, algorithms, and distributed systems design principles; experience with MLOps tools and concepts (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes).
• Bonus: Experience with big data technologies (Spark, Flink, Kafka), familiarity with deep learning frameworks (TensorFlow, PyTorch), contributions to open-source projects related to ML platforms or MLOps, experience with infrastructure-as-code tools (Terraform, CloudFormation).