Senior AI/ML Engineer

VAS; United States; On-site; USD 180,000 - 260,000; Full time

Job summary

VAS is seeking a Senior AI/ML Engineer to lead the development of scalable, real-time AI applications for dairy farming. You will ship AI-enhanced customer solutions and tooling used by engineering teams, turning data into actionable intelligence to feed the world.

You will drive AI enablement, data wrangling, model deployment, observability, and governance, collaborating with product, dairy science, and enterprise leadership to deliver impactful improvements.

Qualifications

• Significant hands-on experience designing, building and deploying production AI/ML solutions.
• Strong experience working with complex data, including distributed systems and legacy datasets.
• Experience with feature engineering, model selection, experimentation and evaluation.
• Proficiency across statistics, operations research, ML and deep learning.

Responsibilities

• Lead AI capabilities and integration in real-time production-grade applications.
• Drive adoption of AI-native engineering practices and governance.
• Build and evolve a Center of Excellence for AI across teams.
• Collaborate with product, dairy science, and engineering leadership to translate requirements into working systems.

Skills

Data wrangling

Feature engineering

Model deployment

Cloud infrastructure

Experiment design

ML frameworks

Production quality systems

Communication

Education

Bachelor's degree in a relevant field

Tools

Databricks

AWS

Job description

Job Description

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.

Responsibilities

AI Enablement

• 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.

Core AI Engineering Skills

• 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.

Evaluation, Testing & Observability

• 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.

Model Fine-Tuning & MLOps

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

Front-end & User Experience

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

Education & Experience

Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical depth and a track record of building and deploying AI/ML solutions in production.

• Significant hands-on experience designing, building and deploying production AI/ML solutions.
• Strong experience working with complex data, including distributed systems, inconsistent schemas and incomplete or legacy datasets.
• Experience with feature engineering, model selection, experimentation and evaluation.
• Strong understanding of descriptive, predictive, prescriptive and generative AI approaches.
• Experience selecting and applying techniques across statistics, operations research, machine learning and deep learning.
• Demonstrated experience taking models from experimentation through production deployment and monitoring.
• Experience with deep learning frameworks and cloud-based AI services.
• Experience with AWS and/or Databricks.
• Experience or exposure to agentic architectures, MCP and AI orchestration frameworks.
• Strong software engineering fundamentals and experience building scalable, production-quality systems.
• Ability to translate ambiguous requirements into working solutions and clearly communicate technical decisions and tradeoffs.
• Bachelor’s degree in Software Engineering, Computer Science, Data Science, AI/ML or a related field preferred.

About Us

For the past 40 years we’ve woken up each day to support those that never stop feeding the world – and we have no plans to quit. We set the standard for farm management solutions and fix our eyes on raising the bar to meet the next generation of expectations.

Our software and information solutions help collect and connect a farm's data – from herd management to feed performance, tracking and more. These insights are a source of truth, empowering producers and their trusted advisors to make profit-driven and sustainable management decisions.

Whether near or far, large or small, VAS is at the heart of your dairy.

VAS has deep roots in the industry through its origin within the URUS family of companies. As a holding company with cooperative and private ownership, URUS is a family of businesses at the heart of the dairy and beef industry – Alta Genetics, GENEX, Genetics Australia, Leachman Cattle, Jetstream, PEAK, SCCL, Trans Ova Genetics and VAS. Each organization has its unique identity, products, and services. These companies work globally to provide cutting-edge dairy and beef genetics, customized reproductive services to maximize conceptions, dairy management information to take producers to the frontline of progressive dairy farming, and an array of products and services to help bovines reach their full genetic potential. URUS has 9 brands in 17 retail countries and employs nearly 2,800 people globally.