Job Title : AI Platform Engineer

Location : Remote

Domain : Artificial Intelligence, Machine Learning Infrastructure, MLOps, Platform Engineering, Kubernetes, GPU Computing, Cloud Infrastructure

About ReXruiters :

At ReXruiters, we help companies connect with highly skilled technology professionals through a skills-first hiring approach. Our platform focuses on evaluating real-world capabilities, technical expertise, and project experience to ensure stronger hiring outcomes. We partner with innovative organizations across industries to identify top talent for critical technology and engineering roles.

About the Opportunity :

Our client is seeking an experienced AI Platform Engineer to design, deploy, and optimize scalable AI/ML infrastructure that powers enterprise-grade artificial intelligence initiatives. This role will focus on building robust AI platforms, automating machine learning workflows, managing GPU-accelerated environments, and implementing MLOps best practices across cloud and hybrid infrastructure.

The ideal candidate will possess strong expertise in Kubernetes, infrastructure automation, GPU orchestration, MLOps tooling, and AI platform engineering, with a passion for enabling data science teams to efficiently build, train, and deploy machine learning models at scale.

Key Responsibilities :

- Strong proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch).

- Hands-on experience with Kubernetes and container orchestration.

- Familiarity with Run:ai or similar GPU scheduling platforms.

- Expertise in Terraform and Ansible for infrastructure automation.

- Experience with Jupyter Notebooks for ML development.

- Knowledge of NVIDIA Enterprise Suite (CUDA, NeMo Framework, Triton, GPU drivers).

- Solid understanding of MLOps principles and tools (e.g., MLflow, Kubeflow).

- Background in deploying and scaling AI workloads in cloud or hybrid environments.

Required Qualifications :

- 4+ years in platform architecture or solutions architecture, with 2+ years focused on AI/ML workloads.

- Experience with high-performance computing (HPC) environments.

- Familiarity with distributed training and model optimization techniques.

- Certification in Kubernetes or cloud platforms (AWS, Azure, GCP).

What We're Looking For :

- Strong problem-solving and troubleshooting capabilities.

- Ownership mindset with a focus on operational excellence.

- Ability to work in fast-paced, cloud-native environments.

- Passion for automation, scalability, and platform engineering best practices.

- Commitment to building secure, reliable, and highly available systems.

Benefits :

- Comprehensive health insurance coverage with dependent coverage options.

- Paid time off, holidays, and additional leave benefits.

- Flexible work arrangements supporting work-life balance.

- Ongoing learning and certification support.

- Employee wellness and well-being programs.

- Statutory and retirement benefits as per applicable regulations.

- Inclusive, collaborative, and growth-oriented work environment.