Who We Are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me , Do the Right Thing , and Get Things Done . These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. About the Opportunity: The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual curiosity and passion for achieving business results. An ability to quickly define the problem, research and leverage state-of-the-art modeling techniques, and provide timely recommendations will be essential. Key skills will include a strong analytical mindset, deep understanding of most popular machine learning algorithms and lead key initiatives with integrity and a passion for investigations, problem solving, and troubleshooting. What You’ll Be Doing : Identify complex fraud patterns and their technical root causes through detailed data mining and analysis, including identification of sophisticated fraud methods employed by actors who are deliberately trying to avoid detection. Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams. Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences. Provide technical guidance for engineering projects that incorporate
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About the Role Together AI is building the AI Acceleration Cloud, an end-to-end platform for the full generative AI lifecycle, combining the fastest LLM inference engine with state-of-the-art AI cloud infrastructure. The AI Infrastructure team at Together AI is at the forefront of building and scaling the foundational systems that power our generative AI platform. The storage and observability team is crucial for designing, implementing, and maintaining robust distributed storage solutions, ensuring seamless data access and management. They are also responsible for developing comprehensive observability platforms, providing critical insights into system performance and GPU utilization, and proactively identifying and resolving issues. Responsibilities Design and implement a scalable observability platform (metrics, logs, traces) using tools like Prometheus, Grafana, ClickHouse, ClickStack, and OpenTelemetry, including telemetry data pipelines and log aggregation workflows. Develop automated monitoring, alerting, and anomaly detection systems, including SLIs/SLOs, runbooks, and predictive analytics for critical services. Build and deploy custom observability tools and infrastructure-as-code using Go, Python, Terraform, Ansible, and Helm. Collaborate with engineering teams to enhance distributed tracing and application monitoring, and lead incident response with post-mortem analysis. Define observability best practices. Requirements Expertise in observability platforms (Prometheus, Grafana, ClickStack, OpenTelemetry) and cloud-native monitoring services (AWS, GCP, Azure). Strong programming skills in Go, Python, or similar languages, with proficiency in infrastructure-as-code tools (Terraform, Ansible, Helm). Experience designing, operating, and scaling large-scale distributed systems and pipelines for high-volume data ingestion and real-time querying. Deep understanding of containerization (Docker) and orchestration (Kubernetes). Knowledge of microservices architectu
Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities Data Pipeline Engineering: Build scalable ingestion pipelines for structured, semi-structured, and engineering data sources. Workflow Orchestration: Develop reliable batch, scheduled, and event-driven workflows using Apache Airflow and cloud-native services. ETL / ELT Frameworks: Implement reusable pipeline patterns, transformations, incremental ingestion, and data quality checks. Schema Management: Implement schema registry, schema versioning, schema evolution, and compatibility controls. Delta Detection: Build change detection and incremental refresh mechanisms for efficient large-scale data synchronization. Entity Extraction: Extract and normalize key identifiers such as Lot, Die, Wafer, Test, Flow, Product, and Step. Cloud Landing Zones: Set up secure AWS, GCP, and on-prem landing targets for validation and analytics pipelines. <
Principal Consultant – Non-Financial Risk (Enterprise Risk) Location: London (Hybrid) | Practice Area: Finance, Risk, Regulatory & Financial Crime | Type: Permanent Lead enterprise-wide risk transformation and shape the future of non-financial risk The Role Capco is seeking experienced Principal Consultants with deep expertise in Non-Financial Risk to join our growing Finance, Risk, Regulatory & Financial Crime (FRRF) capability. In this senior role, you'll lead complex client engagements, advise senior stakeholders, and play a key role in shaping and delivering enterprise and operational risk transformation initiatives. Acting as a trusted advisor, you'll contribute to capability growth, proposition development, and team leadership while leveraging approved AI tools and AI-enabled ways of working to enhance analysis, improve delivery, and strengthen decision-making through responsible AI practices and appropriate human oversight. What You'll Do Lead enterprise and operational risk transformation programmes, helping clients strengthen governance, operating models, controls, and risk frameworks while identifying opportunities to leverage AI-enabled workflows and automation. Oversee trade surveillance and market abuse initiatives, optimising detection scenarios, controls, and monitoring capabilities using data-driven insights and responsible AI techniques where appropriate. Advise senior stakeholders on regulatory expectations and translate complex requirements into practical, strategic solutions that improve enterprise risk management and operational resilience. Apply and oversee AI-enabled analytics and model tuning techniques to enhance risk monitoring, alert calibration, and false positive reduction while ensuring appropriate governance, validation, and human oversight. Build trusted relationships with senior client stakeholders while contributing to business development, proposition development, capability growth, and thought leadership across the Non-Fin
Job Details: Job Description: The Thin Films Senior Process Engineer will support PVD, CVD, and ALD technologies for dielectric and metal thin-film deposition in a high-volume manufacturing environment. Key Responsibilities Apply advanced expertise in thin-film deposition processes to drive continuous improvement in process performance, sustainment, and technology development. Collaborate with upstream and downstream partners to deliver manufacturing improvements through strong cross-functional engagement and stakeholder management. Own manufacturing processes and/or equipment, ensuring achievement of key performance indicators (KPIs) including safety, quality, cost, productivity, defect reduction, and yield improvement. Develop and execute strategic plans for complex projects, coordinating timelines and dependencies across multiple teams and initiatives. Support manufacturing capacity expansion and technology transfer activities to enable successful ramp-to-volume production. Partner with equipment vendors and cross-functional stakeholders to troubleshoot technical challenges, improve tool performance, and enhance operational efficiency. Lead process development initiatives that support current and next-generation high-volume manufacturing technologies. Design and optimize excursion prevention and detection systems to strengthen process control and minimize manufacturing risk. Lead equipment installation, conversion, qualification, and readiness activities during factory ramps, ensuring all tools are deployed safely, on schedule, and in compliance with quality and manufacturing standards. Drive root cause analysis and implement corrective actions to resolve process and equipment-related issues while improving overall manufacturing stability and performance. <p st
Machine Learning Engineer – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like A
Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex
Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper
POSITION SUMMARY: We are looking for a highly motivated Senior Research Associate with a strong focus on process optimization and improvements to join the Molecular Biology product development team, joining a group of scientists who are tasked with developing and advancing Natera’s oncology product portfolio. The Senior Research Associate performs research and/or development tasks in collaboration with others. Makes detailed observations, analyzes data, and interprets results. Investigates creates and develops new methods and technologies for project advancement. Maintains a high level of professional expertise through familiarity with scientific literature. PRIMARY RESPONSIBILITIES: Design, plan, and perform experiments geared towards the development of non-invasive prenatal tests and cancer detection tests. Autonomously and accurately plan and execute complex laboratory experiments Analyze data using advanced analytical tools Keep a detailed laboratory notebook; write protocols and experimental plans, and document results and scientific interpretations Contribute insight toward experimental findings and troubleshoot laboratory processes and protocols Communicate and discuss results with a multidisciplinary team including biologists, bioinformaticians, statisticians, software engineers, and managers Summarize work in research reports and laboratory meeting presentations Learn and understand the science behind ongoing research projects while simultaneously completing increasingly complex tasks. This role will have occasional access to PHI both in paper and electronic form and have occasional access to various technologies to access PHI (paper and electronic) in order to perform the job. The employee must complete training relating to HIPAA/PHI privacy, General Policies and Procedure Compliance training and security training as soon as possible but not later than the first 30 days of hire. Must maintain a current st
P-1125 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 10+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 15+ years of experience building large scale distributed systems with high availability Leadership sk
P-1126 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 7+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 10+ years of experience building large scale distributed systems with high availability Leadersh
P-1126 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 7+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 10+ years of experience building large scale distributed systems with high availability Leadersh
P-1124 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 7+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 10+ years of experience building large scale distributed systems with high availability Leadersh
P-1124 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 7+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection and Response. Experience building systems at large scale internet companies is a huge plus. 10+ years of experience building large scale distributed systems with high availability Leadership
P-1125 Summary At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform. Customers trust Databricks with their most valuable data and Trust & Safety has the mission to build the most trusted data analytics and ML platform in the world. Security Engineering is an integral part of Trust & Safety and has a critical role to play in keeping customer data from bad actors. We are looking for senior leaders such as yourselves to create the vision and define the strategy for this space. The impact you will have: Make Databricks safer for our customers by identifying and plugging key gaps in our infrastructure and services Attract top talent from across the industry. Represent the security engineering discipline throughout the organization, having a powerful voice to make us more data-driven Represent Databricks at academic and industry conferences & events What we look for: 9+ years of experience in Data Security or related areas and expertise in two or more of the following--Cryptography, Kubernetes Security, Web Security, Governance, Privacy, Trust, Safety, Authentication, Identity Management, Access Control, Key Management, Inter-Service Authentication, Secure Application Frameworks, Detection & Response. Experience building systems at large scale internet companies is a huge plus. 15+ years of experience building large scale distributed systems with high availability Le
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