**Company: Fresco Job Description Summary: Senior ML Platform Engineers at Fresco are responsible for designing, building, and maintaining scalable ML infrastructure and services within the KitchenOS platform. They collaborate with scientists, engineers, and platform teams to streamline workflows and ensure efficient model development, deployment, and monitoring. Key responsibilities include developing and maintaining ML infrastructure, building scalable pipelines for data ingestion, preprocessing, training, and deployment, implementing CI/CD pipelines, and optimizing ML workflows for performance and scalability. The ideal candidate has expertise in ML frameworks like TensorFlow, PyTorch, and AWS Sagemaker, experience deploying Large Language Models, proficiency in Python, and strong communication and collaboration skills. They should also have 3+ years of experience delivering consumer-facing ML products, with 2+ years in a senior role, and a strong background in AWS and cloud platforms. In the first 3 months, the expectation is to contribute to the next generation of AI recipe capabilities, and in 6 months, deliver consumer-grade AI services for global markets. Working at Fresco offers the opportunity to join a fast-growing, venture-backed startup, work on a global platform with a competitive compensation and equity package, annual stipend for skill development, flexible hybrid work model, and remote work opportunities for up to 1 month per year. Job Description: About Fresco: Fresco’s KitchenOS is revolutionising the smart kitchen, seamlessly connecting appliances, home cooks, and recipes. With users of smart kitchen appliances expected to reach 248 million by 2027, our platform partners with major appliance brands like BOSCH, Kenwood, and LG to offer an effortless cooking experience. We operate a hybrid model, typically you would be 1 day a week in the office. Your Role: As a Senior ML Platform Engineer, you will design, build, and maintain scalable ML infrastructure and services. Collaborate with scientists, engineers, and platform teams to streamline workflows, ensuring efficient model development, deployment, and monitoring. Key Responsibilities: • Develop and maintain ML infrastructure within the KitchenOS platform. • Build scalable pipelines for data ingestion, preprocessing, training, and deployment, focusing on Large Language Models. • Implement CI/CD pipelines for seamless model deployment. • Optimise ML workflows for… performance and scalability. • Collaborate with scientists and engineers to translate requirements into scalable solutions. Your Skills: • Expertise in ML frameworks like TensorFlow, PyTorch, and AWS Sagemaker. • Strong understanding of AI architecture and ML operations. • Experience deploying Large Language Models and transformer-based architectures. • Proficiency in Python. • Excellent communication and collaboration skills. • Interest in food and IoT is a plus. Your Experience: • 3+ years in delivering consumer-facing ML products, with 2+ years in a senior role. • Proven experience in building and running AI microservices at scale. • Strong background in AWS and cloud platforms. • Effective technical communicator and planner. Expectations: • In 3 months: Contribute to the next generation of AI recipe capabilities. • In 6 months: Deliver consumer-grade AI services for global markets. Why Fresco? • Join a fast-growing, venture-backed startup. • Work with purpose on a global platform. • Competitive compensation and equity. • Annual stipend for skill development. • Flexible, hybrid work model. • Remote work opportunities for up to 1 month per year. Ready to bring your best to Fresco? Get in touch
Company:Fresco
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Level of experience (years):Senior (5+ years of experience)
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
