ML Data Platform Engineer

Do you want to help solve the world's most pressing challenges? Feeding the world's growing population and slowing climate change are two of the world's greatest challenges. AGCO is a part of the solution! Join us to make your contribution.

About the Role

You will be responsible for building the infrastructure to collect, aggregate, and analyze data, supporting an understanding of the performance of our machine learning models. From dataset exploration and curation to performance monitoring and visualization, you’ll ensure the team has the insights needed to create and improve the industry’s best performing models.

You’ll work closely with ML researchers, data scientists, and external partners to:

• Pinpoint weaknesses in model performance.

• Extract actionable insights from our datasets

• Build internal tools & dashboards to explore and monitor model performance.

• Manage and grow the datasets needed to train, evaluate, and improve our models.

We’re looking for someone who is technically strong, independent, and capable of shaping the way we collect, analyze, and use data to drive better machine learning outcomes.

What You’ll Do

• Analyze model outputs to identify failure modes and data gaps.

• Develop tools & processes to select the most impactful data for annotation.

• Design and implement data pipelines for aggregating, cleaning, and curating datasets.

• Work with external vendors & partners to select and use the best tools

• Collaborate with ML & product teams to align data initiatives with model and product goals.

• Build and maintain an internal evaluation platform to store predictions, metadata, and support interactive analysis.

What We’re Looking For

We value independence and creativity — if you’re comfortable defining and executing on a vision for better ML data infrastructure, we want to talk to you.

Required Skills:

• 2+ years of professional experience using Python for data analysis, scripting, and building tools.

• 2+ years of professional experience working with data pipelines and infrastructure in support of machine learning or data-driven products.

• Hands-on experience building and maintaining cloud-based data workflows, preferably on AWS (e.g., S3, Lambda, Step Functions, Glue, Athena).

• Solid understanding of databases and designing schemas for metadata & results (SQL or NoSQL).

Nice-to-have Skills:

• Ability to design and implement internal tools and dashboards, selecting appropriate technologies to meet user needs.

• Experience organizing and managing large datasets, including defining schemas, ensuring data quality, and supporting versioning.

• Strong data operations mindset: building repeatable, reliable workflows and pipelines.

• Familiarity with active learning or data selection strategies.

Why Join Us?

• You’ll have the autonomy to design and own the data platform for ML evaluation and improvement.

• You’ll play a critical role in shaping the future of our ML products by ensuring we’re collecting and using the right data.

• You’ll work at the cutting edge of data and ML infrastructure, solving meaningful problems alongside a collaborative team.

• You will have the opportunity to work closely with customers to deliver the best machine learning solutions in the industry for real-world agricultural challenges.