Applied AI / Machine Learning Engineer

Applico Capital is the leading venture capital firm focused on the $8 trillion B2B distribution industry. Through our learnings and understanding of the industry, we are building a tech startup, currently in stealth, to solve the industry's biggest problems as it comes to unlocking AI-enabled synergies.

Our mandate is to leverage AI and modern technologies to reimagine the role of the traditional distributor and transform how the entire industry operates.

We are looking for highly technical builders who thrive in entrepreneurial, scrappy, and collaborative environments.

We’re seeking an AI Engineer to design, build, and deploy machine learning and generative AI systems that drive tangible impact across core business operations.

You’ll work hands-on to turn prototypes into production systems, embedding AI into products and workflows to improve everything from search and merchandising to pricing, forecasting, and customer support.

This is a deeply technical, highly autonomous role in a startup-style team working directly with stable enterprises as design partners. You’ll move fast, automate aggressively, and deliver measurable value — while partnering closely with data engineers, scientists, and product teams to ensure systems are reliable, safe, and trusted.

You’ll also be expected to leverage AI-augmented engineering practices (LLM copilots, code generation, automated testing) and explore agentic architectures that enable autonomous and semi-autonomous business workflows.

• Build and maintain end-to-end ML and AI pipelines, including training, testing, deployment, and monitoring
• Partner with AI Scientists to translate prototypes and research models into scalable, production-ready systems
• Develop APIs and microservices to integrate AI capabilities directly into business applications and workflows
• Implement automation, testing, and monitoring for reliability, performance, and reproducibility
• Collaborate with Data and MLOps teams to ensure scalability, observability, and cost optimization
• Apply AI-augmented development tools (e.g., GitHub Copilot, GPTs, automated testing agents) to accelerate engineering velocity
• Experiment with and operationalize agentic frameworks (LangChain, AutoGen, CrewAI, N8N, etc.) to orchestrate intelligent, tool-using systems
• Ensure AI systems are governed, observable, and aligned with responsible AI principles

• Build real, production-grade AI systems — not demos — embedded in major operating businesses
• Work alongside leaders in data architecture, automation, and applied AI
• Operate with the autonomy and speed of a startup, backed by the resources of a large, stable enterprise
• Help define how responsible, interoperable, and open AI systems reshape industrial B2B commerce

• 5+ years in software engineering or data engineering, with applied ML experience
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX)
• Strong experience with cloud-native ML platforms (AWS, GCP, or Azure) and modern data systems
• Familiarity with MLOps practices (CI/CD for ML, feature stores, model registries, monitoring)
• Proven ability to deliver production-grade ML systems that create measurable business impact
• Hands-on experience using AI copilots or agent frameworks/orchestration layers (LangChain, AutoGen, CrewAI, N8N, etc.) preferred
• Bonus: familiarity with retrieval-augmented generation (RAG), vector databases, or multi-agent systems