About usRavenPack is the leading big data analytics provider for financial services. Financial professionals rely on RavenPack for its speed and accuracy in analyzing large amounts of unstructured content. RavenPack's products allow clients to enhance returns, reduce risk and increase efficiency by systematically incorporating the effects of public information in their models or workflows. Our clients include the most successful hedge funds, banks, and asset managers in the world!What are we looking for?We are looking for a MLOps Engineer to join a team responsible for building and maintaining the entire ML infrastructure. Taking offline models and turn them into real production systems will be one of the main activities. In addition, designing and developing comprehensive test and monitoring strategies will be also required. The candidate must have all the technical skills for implementing and maintaining the infrastructure in the cloud. The ideal candidate must have a proven track record in MLOps/DevOps or software automation projects and the ability to understand complex software solutions. The candidate will have experience in all phases of the software development life cycle, from requirements gathering, designing CI/CD pipelines, integration testing, monitoring ML models performance, and supporting production systems.The ability to communicate effectively in English both in writing and verbally is a must. Knowledge of Spanish is not a business requirement. European Union's legal working status is required.About youWe want you to be a software passionate, with a strong technical background. You will be facing awesome challenges by covering all the ML development lifecycle stages and using the latest technologies for it.How will you do it?First monthThe onboarding process starts.. You will be having scheduled meetings with the main stakeholders of the different teams in order to get an overall understanding about all company's products and specifically focused on the projects you will be working on. You will start participating in the scrum ceremonies and also reviewing the actual ML processes and infrastructure.After 3 monthsNow you are able to start contributing to the ongoing work related to existing ML infrastructure and start collaborating closely with QAs, ML, and DevOps engineers. Since now you have the overall view of the products and the tech stack, you can propose new initiatives and strategies and start working on them.6 months inNow you are fully aware of all the company products and ongoing projects and you have the know-how to work with them. You became a key member of the team and you are contributing successfully to the different ML development phases. You are creating comprehensive deployment and monitoring strategies in a CI/CD environment. Also, you are able to provide guidance about good practices and collaborate with different teams.Requirements: Experience in applying software engineering concepts and best practices to the entire machine learning development lifecycle including deployments and monitoring of the ML models in production environments. Experience in implementing and optimizing data pipelines for the ML workflows. Experience in designing and implementing CI/CD strategies (e.g., AWS Sagemaker, Azure, Vertex). Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and understanding of machine learning concepts. Proficiency in Python and knowledge in Scripting languages. Database knowledge: SQL and NoSQL. Ability to set priorities and multi-task in a fast-paced environment. Necessary skills to perform root cause analysis when defects occur. Excellent analytical, problem-solving, communication, and interpersonal skills. BSc/BA in Computer Science or Engineering or equivalent experience. Nice to have Experience setting and configuring monitoring and observability alerts. Familiarity with QA processes. Familiarity with LLMs model evaluation. Familiarity with AWS services. Experienced as a software developer or architect. What's in it for you You will work with the latest technologies. You will have ownership of projects working in a collaborative environment where we will value your contribution. You will work in an agile environment able to react quickly to changes with a fairly flat hierarchy. As we encourage continuous learning, we will support your ongoing training. Diversity is in our DNA! You will work in an international environment (over 29 nationalities and 24 languages spoken!)
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