Top Machine Learning Jobs in Lisbon
As a Staff Software Engineer for Machine Learning Infrastructure, you will develop scalable machine learning workflows and backend infrastructure for training, evaluation, and inference, while managing data systems and collaborating with product teams to enhance Snapchat's capabilities.
The Director of Data Science will lead the data science team to support revenue growth through advanced analytics and insights into ad performance, audience engagement, and strategic data projects. They will partner with executives, manage multiple teams, and drive operational improvements using data.
The Software Engineer will work on machine learning infrastructure to enhance Snap's core products, contributing to innovations in augmented reality and messaging technologies. Responsibilities include developing and optimizing machine learning systems, collaborating with diverse teams, and engaging in dynamic in-office collaboration.
Snap Inc is seeking a Machine Learning Engineer with 3+ years of experience to create models driving value for users and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building scalable products. The ideal candidate should have a strong understanding of machine learning algorithms, prioritize tasks independently, and collaborate effectively with partners.
The Machine Learning Engineer at Snap Inc will create models to drive value for users, advertisers, and the company, evaluate technical tradeoffs, perform code reviews, and build robust products. Skills required include strong understanding of machine learning algorithms, ability to prioritize tasks, collaboration skills, and problem-solving abilities.
Create machine learning models to drive value for users, advertisers, and the company. Evaluate technical tradeoffs, perform code reviews, and ensure code quality. Build scalable products iteratively without compromising quality.
Snap Inc. is looking for a Machine Learning Engineer with 5+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, building scalable products, and iterating quickly without compromising quality.
Snap Inc. is seeking a Machine Learning Engineer with 5+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building scalable products. Strong collaboration, problem-solving, and mentorship skills are required.
Featured Jobs
Snap Inc is looking for a Machine Learning Engineer with 3+ years of experience to create models, evaluate technical tradeoffs, perform code reviews, and build scalable products. Strong understanding of machine learning approaches and algorithms is required. Collaborative and mentorship skills are essential.
Snap Inc is looking for a Staff Machine Learning Engineer with 8+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building lasting products. Preferred qualifications include advanced degree in computer science and experience with machine learning frameworks.
Staff Machine Learning Engineer role at Snap Inc, responsible for creating models to drive value for users, advertisers, and the company. Involves evaluating technical tradeoffs, code reviews, and building scalable products with exceptional code quality.
Create models to drive value for users, advertisers, and the company. Evaluate technical tradeoffs, perform code reviews, and prioritize duties to build robust products. Strong collaboration and problem-solving skills required.
Lead a team of machine learning engineers to develop and optimize a personalized video recommendation engine, defining architecture, conducting A/B tests, and improving performance. Mentor team members, collaborate with stakeholders, and ensure high technical standards.
As a Principal Machine Learning Engineer at Snap Inc, you will design and implement machine learning components, develop a next-generation training framework, optimize model training with GPUs, and create an AutoML platform. You will advocate for best practices in system scalability and operational excellence, while influencing technical directions across teams.
The Principal Machine Learning Engineer will design and implement machine learning components, build a large-scale training framework, optimize model performance with GPUs, and develop an AutoML platform. They will collaborate across teams to meet product requirements and ensure high availability and scalability.
As a Machine Learning Engineer at Kalepa, you will be responsible for leading the development and deployment of machine learning models aimed at assessing risks associated with various businesses. You will process structured and unstructured data from diverse sources to generate actionable insights, working collaboratively in a two-week sprint format with a focus on project ownership.
As a Senior Machine Learning Engineer, you will manage the development and optimization of a high-revenue data product, collaborate with data scientists and engineers for efficient workflows, and improve the ML Ops platform infrastructure including data pipelines and CI/CD systems.
As a Senior Machine Learning Engineer, you will lead the development and deployment of machine learning models using large amounts of structured and unstructured data. The role involves understanding business risks and delivering actionable insights through your projects, while collaborating with product management and software engineers in a fast-paced environment.
As a Principal Data Scientist at Zocdoc, you will lead the Search team to enhance their Provider Recommendation System using machine learning algorithms. You will analyze data, interpret results, collaborate with various business partners, and mentor junior data scientists to drive strategic data initiatives in healthcare.
The Senior Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risks. Responsibilities include working with large datasets, collaborating with product management and software engineers, and guiding projects through a two-week sprint cycle.
The Machine Learning Engineering Specialist at ZS will design and implement ML features, collaborate with client teams, write production-ready code, ensure deliverable quality, conduct testing, participate in agile ceremonies, evaluate new technologies, and support project architecture.
The Senior Staff Data Scientist will work closely with the Marketing team to enhance marketing initiatives through statistical modeling and machine learning. Responsibilities include implementing Media Mix Models, conducting performance analysis, building attribution models, and developing dashboards to communicate insights. Staying updated with industry trends and technologies is also crucial.
The Senior Data Scientist in Marketing Analytics will collaborate with the Marketing team to enhance the ROI of marketing initiatives through statistical modeling, machine learning, and data mining. Responsibilities include leading Media Mix Models, establishing marketing measurement frameworks, performing in-depth marketing performance analyses, and developing dashboards to communicate insights.
The Data Scientist will contribute to innovative projects in data science, machine learning, and AI across various sectors, engaging with military and civilian customers to apply cutting-edge technologies and algorithms. They will collaborate with diverse teams, mentor peers, and focus on developing frameworks and tools for mission-critical applications.
As a Machine Learning Engineer at ZS, you'll build and monitor model pipelines, scale algorithms for large datasets, implement ML Ops, write production-ready code, and collaborate with teams to deliver AI-enabled solutions in healthcare. You'll also research new technologies and contribute to the enhancement of ML engineering platforms.
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