Remote Forward-Deployed ML Engineer — Benchmark & Eval

Advatix; Northern (KY); Hybrid; USD 170,000 - 270,000; Full time

Job summary

HRforGrowth is seeking a Forward Deployed Machine Learning Engineer for its US-based team. The role focuses on building AI benchmarks, evaluation systems, and backend infrastructure to support enterprise evaluations across multiple AI domains.

You will own end-to-end projects from feasibility to production, partner with researchers and early customers, and design scalable data pipelines and orchestration for large-scale ML workloads.

Qualifications

• 4+ years of professional engineering experience with hands-on ML model evaluation.
• 3–8 years across ML engineering, evaluation systems, benchmarks, and end-to-end ownership.
• Experience deploying end-to-end ML evaluation or benchmark systems to production for foundation models.
• Hands-on with ML evaluation frameworks and benchmark design (LLM-as-a-judge).
• Ownership of backend and infrastructure: storage and orchestration.
• Experience building benchmarks, evaluations, or data pipelines for LLMs.
• Experience deploying ML systems in production and customer-facing engineering.
• Ability to scope ambiguous problems and deliver solutions.

Responsibilities

• Define, design, and build AI benchmarks and evaluation systems with stakeholders.
• Develop benchmarks and evaluation frameworks across multiple AI domains.
• Build and own backend infrastructure supporting AI model evaluation.
• Design and maintain data pipelines, execution environments, storage, and orchestration.
• Create sandboxed environments for agentic evaluations with tools and multi-step tasks.
• Develop and deploy end-to-end evaluation systems for foundation models.
• Own engineering for customer engagements from requirements to delivery.
• Collaborate with enterprise customers to translate requirements into solutions.
• Identify repeatable evaluation patterns for scalable infrastructure and products.
• Identify infra gaps informing future product development.
• Scope ambiguous problems and drive implementation through delivery.
• Collaborate with AI researchers to translate concepts into production systems.
• Develop scalable systems for large-scale ML evaluation workloads.
• Communicate status, tradeoffs, and solutions clearly to customers and stakeholders.

Skills

ML evaluation

Backend infrastructure

Customer-facing engineering

Data pipelines

Production deployment

Education

Bachelor's degree in Computer Science, Physics, or related technical field

Tools

Storage

Orchestration

Benchmarks

Job description

HRforGrowth is seeking a Forward Deployed Machine Learning Engineer for its US-based team. The role focuses on building AI benchmarks, evaluation systems, and backend infrastructure to support enterprise evaluations across multiple AI domains.

You will own end-to-end projects from feasibility to production, partner with researchers and early customers, and design scalable data pipelines and orchestration for large-scale ML workloads.