ML Platform Engineer (AI)

Location: On-site in New York, NY; relocation support provided

Salary: $210,000–$300,000 per year, plus equity and bonus

Company

hirify.global builds an AI operating system for CPG brands, bringing cash application, deductions, trade, and planning onto one platform.

What you will do

• Own ML pipelines end to end, from experimentation through production, including training, inference, and agentic workloads.
• Build reproducible environments and streamlined paths for AI/ML teams to move models and agents from prototypes to production.
• Develop the cloud foundation as Infrastructure as Code and implement CI/CD for safe ML delivery.
• Serve and optimize inference and forecasting workloads for latency, throughput, and cost, including asynchronous and parallelized processing.
• Design data interfaces with data engineering to provide model inputs and write model outputs back into platform data systems.
• Establish reliability, observability, security, privacy, and production model-quality measurement through online evaluations and human review.

Requirements

• 5+ years of experience in MLOps, ML platform, AI infrastructure, or platform engineering on production ML systems.
• Strong software and infrastructure engineering capabilities, including production code and cloud infrastructure.
• Experience owning and explaining complete production pipelines, including architecture, security, and cost trade-offs.
• Deep understanding of cloud infrastructure, distributed data systems, Infrastructure as Code, CI/CD, and containerized production workloads.
• Strong Python skills and experience working in production application codebases such as Ruby or Java.
• Experience in a fast-moving startup and in productionizing systems developed by research or AI teams.

Nice to have

• LLMOps tooling, including tracing, prompt and version management, and evaluation harnesses.
• Inference optimization with vLLM, ONNX, or TensorRT, plus GPU and spot-instance cost optimization.
• ML platform and orchestration tools such as MLflow, BentoML, Ray, or Airflow.
• Large-scale data systems, vector databases, and managed ML services such as Bedrock, SageMaker, or Vertex AI.
• Production experience with multimodal or generative AI.

Culture & Benefits

• Equity and meaningful ownership in the company.
• Fully paid employee health coverage, plus dental and vision insurance.
• Paid parental leave, fertility and family-forming support, and unlimited PTO.
• 401(k), paid relocation support to NYC, and a fully equipped workspace.
• Catered lunches, team dinners, and snacks and beverages in the workspace.