Duties: Implementation AI projects, from conceptualization to deployment, ensuring high-quality and scalable solutions; Conduct research to identify and apply state-of-the-art AI techniques and algorithms to solve business problems effectively; Design and develop machine learning models, deep learning architectures, and natural language processing algorithms; Collaborate with data engineers and software developers to integrate AI capabilities into existing systems and applications; Evaluate the performance of AI models and optimize them for accuracy, efficiency, and scalability
Requirements: Bachelor's degree in Computer Science, Information Technology, or a related field; 5+ years of experience in AI development, with a focus on machine learning and deep learning; Proven track record of delivering AI projects from inception to production in a fast-paced environment

Duties: Contribute to the 0-1 build of multiple AI products; Design and build high-quality, highly reliable products with user experience at the centre; Be responsible for engineering innovative, best in class AI platforms for the bank; Creating firsts in the Generative AI space for Citi as part of the team that defines the strategic direction for the bank; Continually iterate and scale Generative AI products, whilst listening to the needs of the customers (internal); Mentor and nurture other engineers to help them grow their skills and expertise
Requirements: Deep hands on knowledge of Kubernetes, developing backend platforms and engineering APIs that scale; Fluency in at least two programming language, with preference for Python, Javascript/Typescript, Golang; Experience designing control and sandboxing systems for AI research; Pytorch, TensorFlow experience; Experience maintaining and/or contributing to bug bounty and responsible disclosure programs; Understanding of language models and transformers

Duties: As a Lead ML/Data Learning Engineer Leader in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data
Requirements: Experience leveraging open-source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analyses; At least 10 years of relevant hands-on experience as a Data Engineer in an individual contributor capacity; At least 5 year leading collaborative work in complex engineering projects in an Agile setting e.g. Scrum

Duties: Provide experienced technical expertise to develop process methodology for department to meet internal and external clients’ needs. Plan and coordinate the development of integrated programming solutions serving the full spectrum of statistical programming needs. Provide technical expertise and leadership to the department. Provide internal consulting services, including specifications and user needs analysis for complex project or client requirements
Requirements: Master's/Bachelor's Degree in Life Science/Computer science/Engineering/Statistics/Biostatistics with Min 8+ Years Exp in clinical SAS Programing with hands on SDTM&ADAM/TFL is mandatory; Equivalent combination of education, training and experience in lieu of degree Req; Knowledge of statistics, programming and/or clinical drug development process; Advanced knowledge of computing applications such as Base SAS, SAS Graph and SAS Macro Language

Duties: Work with large-scale structured and unstructured data, build and continuously improve cutting-edge Machine Learning models for Procore product, business, and operational use cases; Evaluate and train Large Language Models (LLMs), traditional language models such as BERT, and other machine learning models such as XGBoost; Hands-on development, production, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases; Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating, and high-performing Machine Learning systems, enabling fast model development, low-latency serving, and ease of model quality upkeep
Requirements: 9+ years of industry experience in applied Machine Learning, inclusive Bachelor/Master or Ph.D. in relevant fields; Exceptional written and verbal communication skills; Strong programming ( Python/Java/C++ or equivalent) and data engineering skills; Strong understanding of the machine learning and data science technical ecosystems (e.g., Tensorflow, Pytorch, MLflow, Ray, LangChain, Data Lakehouse (Databricks), Snowflake, SageMaker, Scikit-learn, etc)