Unity Grow team builds advertising and personalized content delivery solutions used in hundreds of thousands of apps. Our platform processes extensive data sets that are used by machine learning systems living in the core of our various products. Different deep learning techniques are revolutionizing automated decision-making systems and Unity is riding the front wave. Unity is investing heavily in mastering deep learning methodologies and applying them to real-world gaming problems of advertising, engagement, and monetization. In Demand Performance, we develop groundbreaking machine learning centric products. They provide millions of predictions for recommendations each and every second to optimize efficiency and profitability of user acquisition advertising campaigns. Today we are looking for a lead to head up our outstanding team! As a team lead you will have a critical role by running and growing an experienced software development team to build, ship, and operate machine learning powered solutions. This is an excellent chance to create impact by building data and innovative machine learning methods for the benefit of the game development communities.

What you'll be doing

Lead and scale a Data Science team responsible for some of the most critical product models
Enable the team to develop and ship high quality solutions while presenting progress transparently
Help people to grow their talent to build extraordinary machine learning solutions
Identify new ways to redefine advertising in games with machine learning and personalization
Identify novel business opportunities and products

Aura from Unity, a revolutionary large scale mobile platform, is looking for an outstanding and passionate machine learning engineer to join our team.

Join our team and you'll have an opportunity to research, design, implement, and evaluate a variety of advanced ML algorithms using the latest technology.

What you'll be doing

Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models
Transforming data science prototypes and applying appropriate ML algorithms and tools
Build a full ML lifecycle models including model monitoring capabilities
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks

Meta is seeking a Research Engineer to join our Large Language Model (LLM) Research team. We conduct focused research and engineering to build state-of-the-art LLMs, which we often open-source, like our teams recent Llama 2. We are looking for strong engineers who have a background in generative AI and NLP, with experience in areas like language model evaluation; data processing for pre-training and fine-tuning; responsible LLMs; LLM alignment; reinforcement learning for language model tuning; efficient training and inference; and/or multilingual and multimodal modeling.
Research Engineer, Language - Generative AI Responsibilities
Design methods, tools, and infrastructure to push forward the state of the art in large language models.
Define research goals informed by practical engineering concerns.
Contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
Work with a large and globally distributed team.
Contribute to publications and open-sourcing efforts.

Central Applied Science (CAS) is a research and development team, working to improve Metas products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the Meta family of apps. The work we do enhances the Meta family of apps that enable billions of people to communicate with each other daily.

Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, and economics among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at Meta and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise.

We are looking for research interns to join the Product Algorithms team in Central Applied Science. The team is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally increase the magnitude of Metas successes. The ideal candidate will have extensive graduate training in computer science, machine learning, or related disciplines, and the passion to solve real world hard scientific problems. By applying your expertise and passion you will be empowered to drive impact across a range of products, infrastructure and operational use cases at Meta.

Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Central Applied Science (PhD) Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products.
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure.
Work towards long-term ambitious research goals, while identifying intermediate milestones.
Communicate best practices in quantitative analysis to partners.
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value.

Similarweb empowers over 4300 global customers with data-driven insights and competitive benchmarks. We support the digital strategies of companies like Google, eBay, and Adidas. Similarweb went public on the NYSE in 2021 and continues to grow rapidly.

Role Summary:

We are looking for a Senior Software Engineer/ Machine Learning to join our team and help advance our Apps solution. Our product is designed to provide detailed and accurate insights into Apps Analytics, such as traffic estimation, revenue analysis, and app characterization. The role involves constructing and maintaining scalable data pipelines, developing and integrating machine learning models, and ensuring data integrity and efficiency. You will work closely with a diverse team of scientists, engineers, analysts, and collaborate with business and product stakeholders.

Key Responsibilities:

Develop and implement complex, innovative big data ML algorithms for new features, working in collaboration with data scientists and analysts.
Optimize and maintain end-to-end data pipelines using big data technologies to ensure efficiency and performance.
Monitor data pipelines to ensure data integrity and promptly troubleshoot any issues that arise.