Lead AI/ML Engineer

Marlabs Inc.; Northern (KY); Hybrid; USD 130,000 - 185,000; Full time

Job summary

Marlabs Inc. is seeking a Lead AI/ML Engineer to design, build, and scale enterprise AI solutions powering strategic decisions.

You will lead production systems, including RAG, model serving, and governance controls, partnering with data and platform teams to deliver measurable business value. The ideal candidate brings 6+ years in software engineering, deep AI/ML expertise, and experience deploying generative AI in regulated environments.

Qualifications

• 6+ years of software engineering experience in enterprise settings.
• Strong Python and AI/ML framework expertise.
• Experience deploying production-grade AI and NLP solutions.

Responsibilities

• Design, build, and optimize enterprise AI solutions, including RAG and AI-powered decision support.
• Develop and maintain model serving infrastructure, embeddings, and inference pipelines for scalable production workloads.
• Build AI evaluation frameworks to measure accuracy, groundedness, and reliability.
• Implement governance, security, and guardrail controls, including PII protection and prompt injection defenses.

Skills

Software engineering

Python

AI frameworks

Production AI

Cross-functional collaboration

Regulated environments

Tools

Qdrant

pgvector

LlamaIndex

Haystack

Vector databases

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Lead AI/ML Engineer to join our innovative and dynamic team.

Lead AI/ML Engineer | About You

As a Lead AI/ML Engineer, you will be responsible for designing, building, and scaling enterprise-grade AI solutions that power intelligent decision-making and business outcomes. You will lead the development of production AI systems, including retrieval-augmented generation (RAG), model serving, AI orchestration, evaluation frameworks, and governance controls. Working closely with data engineering, platform engineering, and product teams, you will ensure AI solutions are accurate, explainable, secure, and compliant while delivering measurable business value. The ideal candidate combines deep AI/ML expertise with strong software engineering fundamentals and experience deploying production-grade generative AI solutions in regulated or high-stakes environments.

Lead AI/ML Engineer | Day-to-Day

• Design, build, and optimize enterprise AI solutions, including retrieval-augmented generation (RAG), semantic retrieval, model orchestration, and AI-powered decision support capabilities.
• Develop and maintain AI model serving infrastructure, embedding services, vector search platforms, and inference pipelines to support scalable production workloads.
• Build AI evaluation frameworks and testing methodologies to measure model accuracy, groundedness, response quality, reliability, and business performance.
• Implement AI governance, security, and guardrail controls, including PII protection, prompt injection defenses, access controls, model monitoring, and compliance requirements.
• Partner with data engineering teams to integrate governed data sources, semantic layers, and structured-query frameworks that ensure trustworthy and explainable AI outputs.
• Collaborate with product, platform, security, and business stakeholders to define AI product capabilities, optimize performance, and continuously improve AI solution effectiveness.

Lead AI/ML Engineer | Skills & Experience

• 6+ years of software engineering experience, including 2+ years building and deploying production AI, Machine Learning, NLP, LLM, or Retrieval-Augmented Generation (RAG) solutions.
• Strong expertise in Python and modern AI/ML frameworks, with experience developing scalable, production-grade AI applications and services.
• Hands-on experience with LLM technologies, including model serving, vector databases, embeddings, prompt engineering, retrieval pipelines, agent/tool orchestration, and AI workflow automation.
• Experience implementing AI governance and security controls, including model evaluation, guardrails, PII protection, prompt injection prevention, access controls, and responsible AI practices.
• Proven ability to collaborate across data, platform, product, and engineering teams, delivering reliable, explainable, and business-aligned AI solutions in complex enterprise environments.
• Preferred: Experience with self-hosted/open-weight models, vLLM, Ollama, Qdrant, pgvector, LlamaIndex, Haystack, semantic layers, financial services, or other highly regulated industries.