Summary: This role is for a visionary Principal Machine Learning Engineer to lead the end-to-end lifecycle of ML models, solving complex business problems through intelligent systems for high-stakes work. Highlights: 1. Lead ML engineering function and model lifecycle from prototyping to deployment 2. Architect robust ML lifecycles and define strategies for model optimization 3. Collaborate with product managers and mentor team members on AI advancements We are a global technology group built for what's next, offering high calibre professionals the platform for high stakes work, the kind of work that defines an entire career. When you join us, you're not just taking on projects, you're solving problems that don't even have answers yet. You will join an exclusive roster of talent that global leaders, including Google, Snap, Diageo, PayPal, and Jaguar Land Rover call when deadlines seem impossible, when others have already tried and failed, and when the solution absolutely has to work. Forget routine consultancy. You will operate where technology, design, and human behaviour meet to deliver tangible outcomes, fast. This is work that leaves a mark, work you’ll be proud to tell your friends about. We look for people who embody: Innovation to solve the hardest problems. ‍Accountability for every result. ‍Integrity always. Role overview We are looking for a visionary engineer to lead the machine learning engineering function. You will be responsible for the end\-to\-end lifecycle of models that power core product features, from selection and prototyping to large\-scale production deployment. This role requires a blend of deep mathematical understanding and elite engineering skills to solve complex business problems through intelligent systems. As a Principal Machine Learning Engineer at Qodea, you’ll:* Lead the algorithm selection, design, and prototyping of ML models for recommendation and predictive analytics. * Architect robust ML lifecycles, using DAGs and automated pipelines to ensure robustness in production. * Define strategies for model observability, tuning, and optimisation to ensure sustained accuracy post\-deployment. * Collaborate with product managers to define problems and deliver effective AI\-driven solutions. * Mentor team members and stay current with advancements in generative AI and LLM\-based agents. * Guide the integration of ML models into backend flows, ensuring low latency and high availability. Things that will make you stand out:* Extensive experience designing and deploying production\-grade machine learning systems at scale. * Expert\-level programming skills in Python with deep experience in Pandas, Scikit\-learn, TensorFlow, or PyTorch. * Proven experience in areas such as natural language processing, semantic search, or recommendation engines. * Demonstrated ability to lead cross\-functional teams and influence technical roadmaps. * Deep knowledge of large\-scale data processing technologies like Apache Beam, Spark, or Flink. Nice to have:* Experience fine\-tuning and deploying LLMs in production. * Familiarity with vector databases and search technologies like Elasticsearch. * Advanced degree in Computer Science, Statistics, or a related quantitative field. What we want from you: We are building a world\-class delivery centre in Buenos Aires and want the best engineering talent in the region. We believe the best work happens when we collaborate in person. We expect a genuine effort to be present in the office one to two days a week when not on project work to help build our culture and engage in spontaneous problem\-solving. Your energy and presence will be vital in making our studio a hub of creativity and innovation. Benefits We believe in supporting our team members both professionally and personally. Here's how we invest in you: * 10 days PTO \+ 17 days paid public holidays * Pension * Law 19032 (Social Security) * Family allowance * National Employment Fund * Accident Insurance * Life Insurance * Work from Home Allowance * Private Medical Insurance * Birthday leave * 10 paid learning days per year * Bonusly 100 points per month to recognise colleagues