<div><span style="font-size:24px;">About Agreena</span></div><div>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 200 employees across more than 40 nationalities are gathered under the common Agreena flag – either working from our headquarters in Copenhagen, offices in London, or remotely across Europe.</div><div><br></div><div>Agreena provides solutions that drive both environmental and financial sustainability. 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.</div><div><br></div><div><span style="font-size:11pt;">We are looking for an experienced and passionate MLOps engineer to join our team and help us deliver cutting-edge machine learning solutions. You will be responsible for designing, building, and maintaining the infrastructure and pipelines that support the development, deployment, and monitoring of machine learning models at scale. You will be working with multiple data types including satellite imagery data, text and structured data.</span></div><div><br></div><br><br><h3>How will you make an impact:</h3><ul><li>Facilitate the deployment of machine learning-based services created by the data scientists. This involves working in close collaboration with the data science team to comprehend their needs and guarantee seamless integration of their models into the production environment</li><li>Collaborate closely with data scientists, data engineers, and platform engineers throughout the model's lifecycle</li><li>Design and implement scalable and reliable data pipelines and engineering infrastructure to support machine learning systems across different domains and use cases</li><li>Ensure efficient data ingestion mechanisms and design Feature Store like solutions for the streamlined storage of engineered features, enabling seamless access for data scientists</li><li>Apply software engineering best practices and DevOps principles to machine learning, such as version control, testing, automation, CI/CD, etc</li><li>Monitor and optimize the performance, reliability, and accuracy of machine learning models in production. Identify and troubleshoot issues and implement solutions</li><li>Evaluate and adopt new technologies and tools to improve the machine learning lifecycle and workflow</li></ul><h3>Who we’re looking for:</h3><ul><li>Bachelor’s degree or higher in Computer Science, Engineering, Big Data, or a related field.</li><li>Multiple years of experience in MLOps, Data Engineering, or DevOps; with an exposure to MLOps problems</li><li>Proficiency in Python and Bash, and comfortable in a Linux environment</li><li>Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, etc</li><li>Experience in working with cloud platforms and services (AWS and/or GCP), and maintaining cloud infrastructure using tools like Terraform or Ansible</li><li>Experience with Docker, Kubernetes, Kubeflow, and Managed Cloud ML Solutions</li><li>Experience in implementing interfaces (REST API, gRPC, etc.) for machine learning models</li><li>Experience with data processing and storage technologies, such as SQL, NoSQL, Hadoop, Spark, Kafka, etc., and frameworks for data pipelines and workflows like Airflow &amp; Luigi</li><li>Familiarity with machine learning concepts and techniques, such as supervised learning, unsupervised learning, deep learning, etc</li><li>Proven experience and capability of working in a multidisciplinary and multicultural environment</li></ul><h3>What’s in it for you:</h3><ul><li>A unique opportunity to join and help shape a fast-growing tech scale-up with the determination and ambitious mission to reverse climate change</li><li>A truly global environment where you can collaborate and socialise with diverse and passionate colleagues</li><li>Competitive compensation package and holidays</li><li>Team events throughout the year</li><li>An exciting purpose-led culture and mission</li><li>Open communication and supportive feedback culture</li><li>Hybrid or remote working options</li></ul><br><div>🌱<span style="font-size:24px;"> Not quite what you're looking for?</span></div><div>We encourage you to follow our <a href="https://www.linkedin.com/company/agreena/">Agreena LinkedIn</a> page to keep updated on content, articles as well as new opportunities opening. You can also <a href="https://horta.io/jobs/agreena">subscribe to our job alerts talent pool </a>to stay in the loop for the departments you're interested in exploring further at Agreena.</div><div><br></div><div><br></div><div><span style="font-size:24px;">🌍 Be your best-self everyday at Agreena</span></div><div>At Agreena we are devoted to building an environment that promotes equality, inclusion, and diversity. We are on the path towards expansion and growth so with that, we believe everyone’s uniqueness should be celebrated and embraced to help us achieve this exciting journey. This is critical to our success and innovation. We want to build a product that is loved by our customers and we want the same to be reflected in our teams. </div><div><br></div><div>With this in mind, we are working to ensure Agreena remains a diverse and inclusive environment for everyone.  </div>

Agreena is a startup that mints, verifies and sells carbon credits generated by farmers to provide an economic incentive to switch from traditional arable farming to regenerative agricultural methods.


Machine Learning Ops Engineer

<div><span>About Agreena</span></div><div>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 200 employees across more than 40 nationalities are gathered under the common Agreena flag – either working from our headquarters in Copenhagen, offices in London, or remotely across Europe.</div><div><br></div><div>Agreena provides solutions that drive both environmental and financial sustainability. 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.</div><div><br></div><div><span>We are looking for an experienced and passionate MLOps engineer to join our team and help us deliver cutting-edge machine learning solutions. You will be responsible for designing, building, and maintaining the infrastructure and pipelines that support the development, deployment, and monitoring of machine learning models at scale. You will be working with multiple data types including satellite imagery data, text and structured data.</span></div><div><br></div><br><br><h3>How will you make an impact:</h3><ul><li>Facilitate the deployment of machine learning-based services created by the data scientists. This involves working in close collaboration with the data science team to comprehend their needs and guarantee seamless integration of their models into the production environment</li><li>Collaborate closely with data scientists, data engineers, and platform engineers throughout the model's lifecycle</li><li>Design and implement scalable and reliable data pipelines and engineering infrastructure to support machine learning systems across different domains and use cases</li><li>Ensure efficient data ingestion mechanisms and design Feature Store like solutions for the streamlined storage of engineered features, enabling seamless access for data scientists</li><li>Apply software engineering best practices and DevOps principles to machine learning, such as version control, testing, automation, CI/CD, etc</li><li>Monitor and optimize the performance, reliability, and accuracy of machine learning models in production. Identify and troubleshoot issues and implement solutions</li><li>Evaluate and adopt new technologies and tools to improve the machine learning lifecycle and workflow</li></ul><h3>Who we’re looking for:</h3><ul><li>Bachelor’s degree or higher in Computer Science, Engineering, Big Data, or a related field.</li><li>Multiple years of experience in MLOps, Data Engineering, or DevOps; with an exposure to MLOps problems</li><li>Proficiency in Python and Bash, and comfortable in a Linux environment</li><li>Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, etc</li><li>Experience in working with cloud platforms and services (AWS and/or GCP), and maintaining cloud infrastructure using tools like Terraform or Ansible</li><li>Experience with Docker, Kubernetes, Kubeflow, and Managed Cloud ML Solutions</li><li>Experience in implementing interfaces (REST API, gRPC, etc.) for machine learning models</li><li>Experience with data processing and storage technologies, such as SQL, NoSQL, Hadoop, Spark, Kafka, etc., and frameworks for data pipelines and workflows like Airflow &amp; Luigi</li><li>Familiarity with machine learning concepts and techniques, such as supervised learning, unsupervised learning, deep learning, etc</li><li>Proven experience and capability of working in a multidisciplinary and multicultural environment</li></ul><h3>What’s in it for you:</h3><ul><li>A unique opportunity to join and help shape a fast-growing tech scale-up with the determination and ambitious mission to reverse climate change</li><li>A truly global environment where you can collaborate and socialise with diverse and passionate colleagues</li><li>Competitive compensation package and holidays</li><li>Team events throughout the year</li><li>An exciting purpose-led culture and mission</li><li>Open communication and supportive feedback culture</li><li>Hybrid or remote working options</li></ul><br><div>🌱<span> Not quite what you're looking for?</span></div><div>We encourage you to follow our <a href="https://www.linkedin.com/company/agreena/">Agreena LinkedIn</a> page to keep updated on content, articles as well as new opportunities opening. You can also <a href="https://horta.io/jobs/agreena">subscribe to our job alerts talent pool </a>to stay in the loop for the departments you're interested in exploring further at Agreena.</div><div><br></div><div><br></div><div><span>🌍 Be&nbsp;your best-self everyday at Agreena</span></div><div>At Agreena we are devoted to building an environment that promotes equality, inclusion, and diversity. We are on the path towards expansion and growth so with that, we believe everyone’s uniqueness should be celebrated and embraced to help us achieve this exciting journey. This is critical to our success and innovation. We want to build a product that is loved by our customers and we want the same to be reflected in our teams.&nbsp;</div><div><br></div><div>With this in mind, we are working to ensure Agreena remains a diverse and inclusive environment for everyone.&nbsp;&nbsp;</div>

Machine Learning Ops Engineer

About the Job

About the Company

Agreena