Senior Software Engineer – AI/ML Platform

Job Description

Senior Software Engineer – AI/ML Platform | InnovateCorp Solutions

The Tone:
This is a full-time role at InnovateCorp Solutions. The company builds platforms that help businesses globally harness the potential of artificial intelligence and machine learning. This role is central to developing and maintaining the scalable, high-performance infrastructure that supports InnovateCorp Solutions’ machine learning initiatives. It offers significant opportunities for professional growth and contribution to the AI field.

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

• Team: AI/ML Platform team
• Mission: Design, develop, and maintain scalable, high-performance infrastructure and services that underpin machine learning initiatives.
• Tech Stack: Python, Go, Java, SQL, AWS, GCP, Azure, Docker, Kubernetes, PostgreSQL, MongoDB, Redis, Cassandra, Apache Spark, Apache Kafka, Apache Flink, TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, MLflow, Kubeflow, Git, Jenkins, GitLab CI, GitHub Actions.

What You’ll Actually Do
• Lead: Lead the design, development, and implementation of core components for the AI/ML platform, ensuring robustness, scalability, and security.
• Collaborate: Collaborate with data scientists, machine learning engineers, and product managers to translate requirements into technical specifications and architecture designs.
• Develop: Develop and maintain CI/CD pipelines for machine learning models and platform services, ensuring efficient and reliable deployment.
• Implement: Implement and optimize data processing pipelines and feature stores to support large-scale ML training and inference.
• Review: Participate in code reviews, providing constructive feedback and mentoring junior engineers.

The Must-Haves
• Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. This is a mid-to-senior career level role requiring core domain knowledge in backend systems and platform engineering, particularly for AI/ML infrastructure.
• Experience: Minimum of 5+ years of professional experience in software development, with a strong focus on backend systems or platform engineering. This includes practical experience with major cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Skills: Proficiency in at least one of Python, Go, Java, or C++; Demonstrable experience with cloud platforms (AWS, GCP, Azure); Solid understanding of distributed systems, microservices architecture, and API design; Experience with containerization technologies including Docker and Kubernetes; Practical experience with database technologies such as PostgreSQL, MongoDB, Redis, or Cassandra.
• Bonus: Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, or XGBoost; Familiarity with MLOps tools and platforms like MLflow or Kubeflow; Understanding of data warehousing concepts and big data technologies (e.g., Spark, Flink, Kafka); Experience working with streaming data architectures.