Senior AI/ML Platform Engineer

Matrix Global

5d

About The Position

We are seeking a Senior AI/ML Platform Engineer to lead the strategic implementation, scaling, and governance of generative AI and machine learning capabilities across enterprise cloud environments. This senior individual contributor role blends deep technical expertise with strategic execution, focusing on designing, architecting, and delivering production‑grade AI systems using leading cloud AI platforms and enterprise LLM frameworks.
The ideal candidate brings hands‑on experience with large language models, advanced ML engineering, AI security, and MLOps/LLMOps best practices. This role partners closely with engineering, data science, and business teams to deliver high‑impact AI solutions while ensuring adherence to responsible AI and regulatory standards.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, Mathematics, or a related technical discipline.
• 5+ years of hands‑on AI/ML engineering experience, including 3+ years working directly with generative AI and LLM‑based applications.
• 5+ years of senior‑level or executive‑facing experience with the ability to influence senior stakeholders and lead strategic technical initiatives.
• Expert proficiency in Python, including ML frameworks such as PyTorch and TensorFlow, and LLM orchestration frameworks including LangChain and LlamaIndex.
• Extensive experience with enterprise cloud AI platforms, including Azure OpenAI Service, Azure ML Studio, Databricks MLflow, and Google Vertex AI.
• Strong knowledge of MLOps/LLMOps practices, including CI/CD for ML (Azure DevOps, GitHub Actions), infrastructure‑as‑code (Terraform), and containerization (Docker, Kubernetes).
• Experience with real‑time ML inference, streaming data architectures (Kafka, Pub/Sub), and edge deployment for low‑latency applications.
• Hands‑on experience with multi‑modal models, computer vision, and advanced NLP techniques beyond standard LLM text generation.

Responsibilities

• Architect and implement end‑to‑end generative AI solutions using cloud AI ecosystems such as Azure AI and Google Vertex AI.
• Lead development of production-grade LLM applications, including RAG pipelines, prompt engineering, fine‑tuning, LLM grounding, and multi‑agent workflows to achieve measurable business outcomes.
• Implement and maintain AI security controls, such as prompt‑injection defenses, adversarial attack mitigation, data‑poisoning detection, and prompt‑shielding mechanisms.
• Develop solutions for content filtering, output monitoring, and automated AI safety guardrails for generative systems.
• Design and maintain scalable MLOps and AIOps pipelines, ensuring automated retraining, model versioning, observability, and explainability with high service availability (99.9%).
• Translate strategic objectives into actionable AI/ML Proof‑of‑Concepts and production systems, demonstrating ROI through iterative development and rapid prototyping.
• Shape technical strategy for expanding AI/ML capabilities across hybrid cloud environments, assessing emerging technologies such as small language models, agentic AI, and edge inference.
• Provide mentorship and technical leadership to platform engineers and data scientists on advanced ML, LLMOps, and responsible AI methodologies.
• Conduct technical evaluations and due diligence of AI vendors and tools, including emerging technologies such as Cohere, Anthropic, and open‑source LLM ecosystems.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level