The Role
The AI Platform Engineer will design and optimize AI/ML infrastructure, automate pipelines, and manage Kubernetes for effective machine learning model deployment and collaboration.
Summary Generated by Built In
AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
We are seeking an experienced AI Platform Engineer to design, deploy, and optimize AI/ML infrastructure, AI workflows, and automated pipelines. This role focuses on building scalable environments for training and deploying machine learning models, leveraging modern orchestration, automation, and GPU acceleration technologies. You will collaborate with data scientists and platform engineers to drive efficient resource utilization and scalable operations across cloud and hybrid environments.
Key Responsibilities
- Kubernetes for AI/ML: Architect and manage Kubernetes clusters tailored to AI/ML workloads.
- GPU Orchestration: Implement Run:ai and operators for GPU resource orchestration and workload scheduling.
- Automation & Pipelines: Develop and maintain Python-based automation scripts and ML pipelines; automate infrastructure provisioning with Terraform and configuration management with Ansible.
- Notebooks & Collaboration: Create and manage Jupyter Notebooks for experimentation and collaboration.
- NVIDIA Integration: Integrate and optimize NVIDIA Enterprise Suite components (CUDA, NeMo Framework, Triton, TensorRT, GPU drivers) for accelerated computing.
- MLOps Practices: Establish and maintain MLOps best practices for model lifecycle management, CI/CD, and monitoring (e.g., MLflow, Kubeflow).
- Collaboration: Work closely with data scientists and platform engineers to ensure efficient resource utilization and scalability across environments.
Required Skills & Experience
- 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.
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).
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
India Employment Benefits include:
Comprehensive health insurance coverage for employees, with options to extend coverage to dependents
Paid time off and company holidays, along with additional leave benefits as per policy
Flexible work arrangements, supporting work-life balance
Learning and development opportunities to support continuous growth and upskilling
Employee wellness initiatives and programs focused on physical and mental well-being
Retirement and statutory benefits in line with India regulations
Inclusive and people-first culture, with a strong focus on collaboration and ownership
Skills Required
- Strong proficiency in Python and experience with ML frameworks
- 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)
- 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)
AHEAD Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AHEAD and has not been reviewed or approved by AHEAD.
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Retirement Support — 401(k) contributions are matched dollar-for-dollar on the first $5,000 each year, with matching made each pay period and immediate 100% vesting. This structure signals above-standard employer support for retirement savings.
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Affordable Benefits — Medical options include low employee premiums for PPO and HDHP plans, and the HDHP adds employer HSA funding plus a dollar-for-dollar HSA match up to stated amounts. Dental and vision plans list very low per-paycheck costs, helping keep overall healthcare spend manageable.
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Wellbeing & Lifestyle Benefits — No-cost telemedicine (including virtual mental health when enrolled), free Calm access for the employee and dependents, and an EAP with counseling are included. Company-paid life and disability plus voluntary protections (legal/ID, pet insurance) and other extras round out a comprehensive set of supports.
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The Company
What We Do
AHEAD builds platforms for digital business. By weaving together cloud infrastructure, intelligent operations, and modern applications, we help enterprises deliver on the promise of digital transformation.
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