Data & AI Lead & Upside Robotics

Who Is Upside Robotics & How Are They Changing the World?

Upside Robotics is transforming modern agriculture with AI-powered, autonomous field robots that deliver water and nutrients directly to plant roots; cutting fertilizer waste, improving yields, and reducing environmental impact. Founded in Kitchener-Waterloo, they’re backed by world-class investors and already partnering with Ontario farms to prove what sustainable, high-efficiency farming looks like in practice.

How Will I Make An Impact?

Upside Robotics has reached a critical inflection point: they now have large-scale, real-world plant and field data. This role exists to take ownership of that data and turn it into defensible insight and long-term company IP.

As Data & AI Lead reporting to the CTO, you will work at the intersection of data, statistics, and applied machine learning to understand why plants respond the way they do across different conditions: soil, weather, timing, and treatment. Your work will lay the foundation for how Upside reduces fertilizer use and improves yields.

You’ll work closely with our plant science expert to analyze results, validate trends, and build systems that continuously learn over time.

What you’ll do:

• Take ownership of Upside’s growing datasets and extract statistically meaningful insights from them
• Design and implement scalable data analysis pipelines using Python and SQL
• Identify patterns, correlations, and trends across multivariate, real-world datasets
• Apply machine learning, optimization, or reinforcement learning techniques where appropriate
  Distinguish signal from noise and evaluate statistical relevance of results
• Translate experimental results into durable, repeatable intelligence
• Help define what “good data” and “good outcomes” look like as the system matures
• Collaborate with plant science and engineering teams to turn analysis into long-term learning systems

How Do I Know If This Is For Me?

• You’re curious about and excited by ambiguous, real-world problems where the data is imperfect but the impact is massive
• You enjoy building models that actually change physical outcomes, not just dashboards
• You think in systems: data → model → decision → outcome → learning loop
• You’re as comfortable exploring data as you are productionizing insights
• You want to own something end-to-end, not just tune models handed to you

Our Ideal Candidate Looks Like:

• Proven experience working with large, complex datasets and producing meaningful results from them
• Strong judgment around statistical significance, relevance, and validation
• Excellent Python and SQL skills
• Experience applying machine learning or quantitative methods beyond surface-level tooling
• A track record of curiosity, ownership, and self-directed problem solving

Nice-to-have:

• Experience with reinforcement learning, optimization, or traditional AI techniques
  Exposure to environmental, agricultural, or physical-world data
• Experience building systems that improve over time

Location and Working Model: 

This role requires in-office collaboration approximately 1 day per week in the off-season (October - April). The office is located in Kitchener-Waterloo. 

From May through October, you’ll also spend regular time in the field at farms across Ontario (Owen Sound → Sarnia corridor). 

Because agriculture is seasonal and weather-driven:

• Hours are less predictable in the growing season. Sunny days mean long days in the field; rainy days mean downtime.
• Off-season (Nov–Apr) looks more like a standard 9–5 schedule focused on architecture, simulation and readiness. 
• You should genuinely enjoy being outdoors - walking fields, troubleshooting robots, and seeing your code impact crops! 

‍We understand, accept, and value the differences between people of different backgrounds, genders, sexual orientations, ages, beliefs, and abilities. We are happy to make any accommodations you may need throughout the interview process.  We aim to create an inclusive environment and encourage diverse individuals to apply.

The Process:

• Screening conversation with Carly at Artemis Canada
• Intro conversation with the CEO (values, culture, motivation)
• Technical deep dive with the CTO
• Practical working session (modeling, data reasoning, or design exercise)
• Final meeting (onsite/shop/field visit, where possible)

Your Artemis Canada partner, Carly,  will work closely with you throughout every step of the process.

We’d love to hear from you - even if you don’t meet 100% of the requirements! Send a note to Carly@artemiscanada.com if you  or someone you know is interested!