Senior Machine Learning Engineer

Agreena is an exciting, dynamic, and purpose-oriented organisation united in a mission to mobilise farmers and corporations to unlock the value of nature and help restore the planet. While we're rooted in agriculture, finance, and technology, our team of experts range from soil carbon scientists and software developers to market strategists and regulatory affairs experts. Over 160 employees across more than 30 nationalities are gathered under the common Agreena flag – either working from our headquarters in Copenhagen, offices in London, or remotely across Europe.

As a rapidly scaling climate agtech, Agreena provides solutions that drive both environmental and financial sustainability in farming. We have helped farmers across 20 countries in their journey from conventional agriculture to regenerative farming practices to reduce greenhouse gas emissions and remove CO2 from the atmosphere, storing it in soil. Our company offers a supportive and positive work environment with opportunities for learning, leading and growth no matter where you are in your professional journey. We believe in giving our employees a lot of responsibility, and we encourage new thinking, innovation and fun.

And this is where you come in:

At Agreena, we are building the technological and financial infrastructure to support farmers in their transition to regenerative agriculture. We monitor, report, and verify (MRV) soil carbon at a planetary scale, creating high-integrity carbon credits to finance the green transition.

We are looking for a strategic Senior Machine Learning Engineer to build the backbone of our "planet-scale" intelligence platform. You won't just use models; you will build the high-performance, distributed systems that allow us to train, fine-tune, and serve them at a scale. This is a unique opportunity to apply SOTA AI to one of the most urgent challenges of our time: food security and climate change.

What You'll Build & Own:

• Planet-Scale ML Platform: You will drive development of our distributed ML platform using Ray, including building new capabilities and improving efficiency across our suite of pipelines. Your goal is to create a robust, scalable architecture that can process terabytes of geospatial and multi-modal data.

• SOTA Model R&D: You will experiment with, train, and deploy state-of-the-art Computer Vision models (for satellite/remote sensing data) and NLP models (for processing agricultural and scientific texts) to power our MRV-platform.

• Foundational Model Factory: You will build and refine our pipelines for fine-tuning foundational models (e.g., using PEFT, LoRA) to create expert models specialised in agronomy, soil science, and remote sensing.

• AI Agent Ecosystem: You will pioneer the development of autonomous AI Agents. This includes building the critical observability, monitoring, and evaluation frameworks (LLM-ops) to ensure our agents are reliable, accurate, and continuously improving.

This Role is for You If:

• You have 5+ years of experience in a Machine learning engineer role.

• You have a deep hunger to build and ship reliable systems, not just run experiments.

• You are passionate about solving hard, meaningful problems. The idea of applying your skills to climate-tech and agriculture excites you.

• You are a highly collaborative and eager teammate who believes the best work happens when everyone "goes the extra mile" for a shared mission.

• You demonstrate high levels of ownership and thrive in an environment where you are given the strategic context and the autonomy to deliver.

Core Qualifications:

• Demonstrable, hands-on experience building and scaling distributed ML systems. We use Ray on Anyscale, so if you have experience with Ray, that is a big plus.

• Experience in training or fine-tuning SOTA models in at least one (preferably both) of the following domains: Computer Vision (CV) or Natural Language Processing (NLP).

• Knowledge around the modern AI stack, including fine-tuning foundational models and an understanding of techniques like RAG, PEFT, and LoRA.

• Familiarity with building agentic systems (e.g., using frameworks like LangChain, LlamaIndex, Pydantic AI) and the MLOps/LLM-ops tools required to monitor them (e.g., Weights & Biases, Arize, TruEra, Logfire).

• Experience shipping a project from ideation to production, owning the deployment and liaising with product teams.

• Technical leadership relating to internal tooling, code quality, processes and standardisation. You have led initiatives to adopt new tools and techniques.

• Bonus Points: Experience with geospatial data (e.g., satellite imagery, GIS) or a background in agriculture/climate-tech.

What's in it for you:

• A unique opportunity to join and help shape a fast-growing tech scale up with the determination and ambitious mission to reverse climate change;

• A truly global environment where you can collaborate and socialise with diverse and passionate colleagues;

• Competitive compensation package and holidays;

• Centrally located modern office in Copenhagen or London and the option to work from home a couple days a week;

• Team events throughout the year;

• An exciting purpose-led culture and mission;

• Open communication and supportive feedback culture.

Stay connected with us by following our Agreena LinkedIn page. It's the best way to stay updated on our latest content, articles, and exciting new opportunities.

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At Agreena, we are devoted to building an environment that promotes equality, inclusion, and diversity. As we embark on our journey of expansion and growth, we recognise the value of celebrating and embracing everyone's uniqueness. This diversity is crucial to our success and innovation. We aspire to build a product that is loved by our customers and we want the same to be reflected in our teams. 

With this in mind, we're dedicated to ensuring that Agreena remains a welcoming and diverse environment for all.