Senior AI​/ML Engineer

Turn decades of data into intelligence that helps feed the world.

VAS is the Operating System of the modern dairy with decades of longitudinal data for the most productive cows in the world. We hold a dominant US market position, and an expanding global reach.

We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade applications that use AI/ML models to drive actionable intelligence on dairy farms. This is a strategic, hands‑on position for an experienced technical leader who has a track record of shipping AI‑enhanced customer applications and tooling used by engineering teams.

Our highly customizable on‑farm systems give dairy owners unmatched flexibility in how they run their business. The right candidate sees that as a data challenge, where others will see it as an unsolvable mess.

• Understand customer challenges and how integrating AI capabilities can help lead to solutions that have AI as a differentiator.
• Identify opportunities to apply AI for efficiency, growth, and customer value
• Drive awareness of AI capabilities and demonstrate how it can address customer needs, improve efficiency, reduce costs, and drive growth
• Drive transformation from AI-Ad Hoc to AI-Native engineering practices
• Serve as an AI technical SME, conduct R&D to meet the needs of our AI strategy
• Continuously assess emerging AI tools and make data-driven recommendations
• Measure & Accelerate Adoption:
  Establish KPIs, track progress from the current to 100% adoption, implement interventions to accelerate uptake and communicate impact
• Build Center of Excellence:
  Create forums for knowledge sharing, celebrate wins, and foster peer-to-peer learning
• Cross-functional communication, explaining technical tradeoffs to product, dairy science, and engineering leadership in plain language.
• Working with other enterprise stakeholders, establish AI governance frameworks and guardrails covering compliance, security, privacy, and ethical AI practices, and embed them into development workflows

• Comfort across the full method spectrum, from classical statistics and operations research through machine learning to modern generative AI, choosing the simplest tool that solves the problem.
• Data-wrangling skill with messy, distributed, legacy enterprise data sources, including inconsistent schemas and incomplete records.
• Feature-engineering and data preprocessing for both structured farm data and unstructured sources.
• Model selection and evaluation, knowing when linear regression, optimization, or a lookup table beats a neural network.
• Production deployment experience, shipping models into real time applications rather than notebooks.
• Cloud AI infrastructure fluency, specifically Databricks and AWS.
• Experiment design and statistical rigor, being able to prove a model or method actually improves outcomes.
• Translating ambiguous business or technical requirements into working systems.
• Agentic and MCP experience

• Build unit and behavioral tests for agents, tools, and workflows.
• Develop tooling for trace analysis, agent state debugging, and hallucination tracking.
• Compare and benchmark agent orchestration frameworks for trade-offs in speed, reliability, and usability.

• Integrate, deploy, fine tune and monitor models in production using cloud providers.
• Set up agent logging, observability dashboards, and recovery workflows.

• Collaborate with front-end developers or build user-facing components using React, Type Script.
• Ensure seamless user and agent interaction via UI and API bridges.

Your background might include software engineering, data engineering, data science,…