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interos.ai · 1 day ago

Lead Machine Learning Engineer

United States

Full-time

Remote

Senior Level, Lead/Staff

$200K/yr - $240K/yr

8+ years exp

Interos.ai is the supply chain risk intelligence company focused on building trusted and transparent supply chains. They are seeking a Lead Machine Learning Engineer to serve as a technical architect for their ML team, responsible for developing AI-powered agents and integrating AI solutions into their product.

Artificial Intelligence (AI)Cyber SecurityMachine LearningRisk ManagementSaaSSupply Chain Management

No H1B

Responsibilities

Develop AI-powered agents that integrate deeply into Interos.ai product experience

Understanding of AI Lifecycle: Comprehensive knowledge of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation

Evaluate, select, and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance

Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation

Define best practices for agent design, security, and governance in AI-driven enterprise applications

Work with product, engineering, and data science teams to design and implement AI-based automation solutions

Identify new opportunities to embed AI into the Interos.ai platform

Establish monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time

Qualification

Machine LearningAI FrameworksPythonCloud Services (AWS)Data PrivacyData LakesProblem-SolvingTeam Collaboration

Required

8+ years of experience in Software development

5+ years of experience in AI, machine learning, with a focus on enterprise applications

Deep understanding of LLMs, AI agents, and orchestration frameworks (e.g., LangGraph)

Experience with enterprise-grade AI architectures, API integration, and large-scale automation

Proficiency in Python, cloud services (AWS), and AI model deployment

Strong problem-solving skills and the ability to translate business needs into AI-powered solutions

Experience in data privacy, security, and compliance for AI in enterprise environments

Experience in Data lakes such as Snowflake and Databricks

Preferred

Masters/Doctorate degree in a relevant field, such as Computer Science, Mathematics, or Engineering

Experience developing and deploying machine learning solutions using large-scale datasets, including specification design, data collection and labeling, model development, validation, deployment, and ongoing monitoring

Hands-on experience with vector databases, retrieval-augmented generation (RAG), and fine-tuning LLMs

Experience with fine-tuning models including identifying and curating datasets as well as experimenting with models for iterative improvement