Machine Learning Operations Engineer

About Agreena Agreena is an exciting, dynamic, and purpose-driven organization with a mission to mobilize farmers and corporations to unlock the value of nature and restore the planet. Though our foundation is in agriculture, finance, and technology, our expert team consists of soil carbon scientists, software developers, market strategists, and regulatory affairs experts. We have over 200 employees from over 40 nationalities all working together under the Agreena banner, whether it be from our Copenhagen headquarters, our London offices, or remotely across Europe. Agreena provides solutions that drive both environmental and financial sustainability. We promote a positive and supportive work environment featuring opportunities for learning, leading, and growth, regardless of where you are in your professional journey. We trust our employees with significant responsibility, and we foster an atmosphere of innovative thinking, and fun. We are seeking an experienced and dedicated MLOps engineer to join our team and help us deliver state-of-the-art machine learning solutions. You will be tasked with designing, constructing, and maintaining the infrastructure and pipelines that facilitate the development, deployment, and monitoring of machine learning models at scale. You will work with multiple data types, including satellite imagery data, text, and structured data. How will you make an impact: - You will facilitate the deployment of machine learning services created by our data scientists, collaborating closely with the data science team to understand their needs and ensure their models are seamlessly integrated into our production environment. - Collaborate closely with data scientists, data engineers, and platform engineers throughout the model lifecycle. - Design and implement scalable and reliable data pipelines and engineering infrastructure to support machine learning systems across various domains and use cases. - Ensure efficient data ingestion mechanisms and design solutions for the streamlined storage of engineered features, enabling seamless access for data scientists. - Implement software engineering best practices and DevOps principles to machine learning, such as version control, testing, automation, CI/CD, and more. - Monitor and optimize the performance, reliability, and accuracy of machine learning models in production. Identify and troubleshoot problems, and implement solutions. - Evaluate and adopt new technologies and tools to improve the machine learning lifecycle and workflow. Who we’re looking for: - A Bachelor’s degree or higher in Computer Science, Engineering, Big Data, or a related field. - Multiple years of experience in MLOps, Data Engineering, or DevOps, with a focus on MLOps problems. - Proficiency in Python and Bash, and comfortable in a Linux environment. - Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, Scikit-learn, etc. - Experience with cloud platforms and services (AWS and/or GCP), and maintaining cloud infrastructure using tools like Terraform or Ansible. - Experience with Docker, Kubernetes, Kubeflow, and Managed Cloud ML Solutions. - Experience in implementing interfaces (REST API, gRPC, etc.) for machine learning models. - Experience with data processing and storage technologies, such as SQL, NoSQL, Hadoop, Spark, Kafka, etc., and frameworks for data pipelines and workflows like Airflow & Luigi. - Familiarity with machine learning concepts and techniques, such as supervised learning, unsupervised learning, deep learning, etc. - Demonstrated experience and capability of working in a multidisciplinary and multicultural environment. What’s in it for you: - A unique opportunity to join and help shape a rapidly growing tech scale-up with a determined and ambitious mission to combat climate change. - A truly global environment where you can collaborate and socialize with diverse and passionate colleagues. - A competitive compensation package and holidays. - Regular team events throughout the year. - An exciting culture focused on a purpose-driven mission. - An open communication and supportive feedback culture. - Options for hybrid or remote working. Not exactly what you're looking for? Feel free to follow our Agreena LinkedIn page for updates on content, articles, and new opportunities. If you're interested in exploring more at Agreena, you can also subscribe to our job alerts talent pool. Be your best self every day at Agreena At Agreena, we are committed to creating an environment that promotes equality, inclusion, and diversity. As we are on the verge of expansion and growth, we believe that everyone's unique characteristics should be celebrated and incorporated to help us on this exciting journey. This is vital for our success and innovation. We aim to create a product that our customers will love, and we want our teams to reflect that same affection. With this in mind, we are working to ensure that Agreena continues to be a diverse and inclusive environment for everyone.