Senior ML Platform Engineer

at  Fresco

What started with a shared love of food and technology has evolved to become the only neutral, cross-brand platform that seamlessly brings appliances, home cooks, and recipes together–Fresco’s KitchenOS.
Smart kitchen appliance users are expected to reach 248 million worldwide by 2027. The Fresco KitchenOS platform is designed to facilitate the transition to that future for both appliance makers and home cooks. Fresco connects any compatible appliance, across brands so that users can focus on what they do best, preparing meals and are committed to building the best possible cooking experience.
From iPads and smart speakers to appliance screens and smart home assistants, Fresco delivers an effortless cooking experience and connects dots in the kitchen. Fresco partners with the appliance makers like BOSCH, Kenwood, Instant Brands, GE Appliances, Electrolux, LG, Thermomix and Panasonic and are growing fast.
Founded in 2012, Fresco currently operates globally and has offices in Dublin, Ireland, and Spain.
As a Senior ML Platform engineer, you will be responsible for designing, building and maintaining robust and scalable ML infrastructure and services. You will work closely with applied scientists, ML engineers and Platform teams to streamline ML workflows, ensuring efficient model development, deployment and monitoring.

YOUR SKILLS:

• You have deep knowledge and experience with ML frameworks and Libraries such as Tensorflow/TFX, PyTorch, TorchServe, Tensorflow Serving and or Hugging Face as well as managed services such as AWS Sagemaker.
• You have a deep understanding of AI Architecture and ML Operations and know how to navigate common pitfalls in AI service design and scaling
• You have experience deploying Large Language Models and Transformer-based model architectures, particularly open-source LLM model families such as Llama and BERT.
• Well-versed with Model Development Lifecycle from initial ad hoc analysis in notebooks to monitored services in production environments.
• You have the ability to communicate to stakeholders and collaborate effectively within a cross-functional team.
• Strong programming skills in Python
• A love of food and interest in IoT is an advantage.

YOUR EXPERIENCE:

• You have 3+ years delivering real-world consumer-facing machine learning products and services, with at least 2 years in a senior role.
• Demonstrated experience in architecting, building and running AI microservices and ML infrastructure at scale.
• Strong background on Cloud Platforms (specifically AWS).
• Strong technical communicator, with situational communication skills across technical peers as well as less technical stakeholders.
• Experience within planning, resource allocation and ability to manage and implement agile development processes.

WHAT YOU’LL GET.

• The chance to work at a hyper-growth, venture-backed startup in a budding industry
• The ability to feel true purpose in your work and generate success on a global platform
• Competitive compensation
• Meaningful share options as part of our Employee Share Option Scheme
• A stipend each year to level up your skills–courses, conferences, books, screencasts, or whatever challenges you
• A flexible, hybrid work model to suit your needs
• The opportunity to work remotely from anywhere in the world for up to 1 month per year
  Just like the ingredients in our kitchen, we believe that diversity of ideas is what makes the workplace great. Fresco is proud to be an equal opportunities employer, and we are committed to building a diverse and inclusive workplace. We welcome and encourage applications from candidates from a range of national, ethnic, or cultural groups. This job description works as a guide for the caliber of person we need, but we also understand that skills are transferable. If you are an exceptional candidate with mismatching experience, please apply and explain why you would be a great fit for Fresco

• Design, develop and maintain the ML platform within Fresco KitchenOS Platform.
• Design, develop and maintain scalable ML pipelines for data ingestion, preprocessing, training, validation and deployment with a particular focus on Large Language Models.
• Design, develop and maintain ML platform features, model registries, serving frameworks, features stores, vector DBs and other ML infrastructure components
• Work with ML engineers to design, develop and maintain consumer-scale ML production services.
• Implement CI/CD pipelines for ML models, ensuring automated and seamless deployment
• Optimise ML workflows for performance, scalability and efficiency
• Implement monitoring and alerting systems to track model performance, data and infrastructure health.
• Collaborate with Applied scientists and ML engineers to understand requirements and translate them into scalable solutions.