Senior Ai Ml Operations Engineer Jobs

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. The Heterogeneous Integration Group (HIG) sits within the Technology and Products Group (TPG). We are developing High Bandwidth Memory (HBM) solutions for AI and ML applications! We stack multiple DRAM chips on a high-speed memory controller using TSV (Through Silicon Via) technology, dramatically increasing memory density and bandwidth. Our designs span custom digital and RTL2GDS flows, and we are targeting the lowest power per bit in the industry. Join us as a Senior Verification Engineer and contribute to modular, scalable verification solutions for next-generation HBM DRAM products! You will work independently within a multi-functional team of technical domain experts, spanning both IP-level and SoC-level verification. You will collaborate with Design Engineering, Product Engineering, and Business Units to complete the HBM verification roadmap. You will apply your solid understanding of testbench architecture, custom or SoC verification methodologies, and 2.5D & 3D package integration to evaluate issues, define solutions, and broaden your expertise. Responsibilities: Develop and implement verification plans and architecture collateral across IP-level and SoC-level verification for current and future HBM designs Support co-verification of the overall system and participate in customer interactions to gather feedback and provide recommendations for future HBM solutions Build and improve verification methodology components and GenAI applications aligned to HBM design cycles, broadening cross-disc

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. We are part of the Heterogeneous Integration Group within Technology and Products, where we build High Bandwidth Memory solutions that power AI and ML platforms. Our team works at the edge of what’s possible, stacking and integrating advanced silicon technologies to deliver industry‑leading bandwidth, density, and power efficiency. We move fast, solve hard problems, and set technical direction others follow! This role sits at the center of next‑generation HBM development. As a senior SI/PI technical authority, you will shape system‑level decisions that directly impact performance, reliability, and scalability across multiple product generations. If you enjoy deep technical ownership, complex problem solving, and influencing architecture from concept to sign‑off, this role offers both challenge and impact. This role supports the design and deployment of AI-enabled solutions that improve efficiency and decision-making. Responsibilities: Lead signal integrity channel analysis for 2.5D and 3D silicon interposers, including frequency‑ and time‑domain evaluation Define and drive power delivery architecture, impedance targets, and transient analysis Perform electromagnetic extraction and modeling across PCB, package, and interposer designs Establish SI/PI standards, methodologies, and sign‑off criteria for HBM system designs Provide clear technical direction in ambiguous or incomplete design environments Minimum Qualifications: 7 years of experience in

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. The Heterogeneous Integration Group (HIG) within Micron's Technology and Products Group (TPG) leads the development of High Bandwidth Memory (HBM) solutions for AI and ML applications. Our modern designs use Through Silicon Via (TSV) technology. We stack multiple DRAM chips on a high-speed memory controller with a coordinated logic chip in one package. This new way improves memory density and bandwidth through parallelization. It aims to deliver the lowest power per bit solutions in the industry. As a Static Timing Analysis (STA) Engineer — you will be part of the Heterogeneous Integration Group (HIG), owning chip-level timing sign-off for next-generation die. You will work closely with RTL design, physical design, architecture, DFT, verification, and product teams to ensure timing integrity and drive timing closure across all modes and corners from initial design through tape-out. This is a hands-on senior technical role focused on chip-level STA ownership, constraint authoring, timing closure, methodology development, and pre-/post-silicon timing correlation. Key Responsibilities Responsibilities will include, but are not limited to: Own end-to-end chip-level static timing analysis and sign-off across all checks, modes, corners, and voltage and temperature conditions. Develop, maintain, and validate sign-off quality Synopsys Design Constraints (SDC) for clocks, resets, high-bandwidth memory (HBM) interfaces, design for test (DFT), and configuration logic. Drive timing closure at block, sub

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. The Heterogeneous Integration Group (HIG) within Micron's Technology and Products Group (TPG) leads the development of High Bandwidth Memory (HBM) solutions for AI and ML applications. Our modern designs use Through Silicon Via (TSV) technology. We stack multiple DRAM chips on a high-speed memory controller with a coordinated logic chip in one package. This new way improves memory density and bandwidth through parallelization. It aims to deliver the lowest power per bit solutions in the industry. As a Static Timing Analysis (STA) Engineer — you will be part of the Heterogeneous Integration Group (HIG), owning chip-level timing sign-off for next-generation die. You will work closely with RTL design, physical design, architecture, DFT, verification, and product teams to ensure timing integrity and drive timing closure across all modes and corners from initial design through tape-out. This is a hands-on senior technical role focused on chip-level STA ownership, constraint authoring, timing closure, methodology development, and pre-/post-silicon timing correlation. Key Responsibilities Responsibilities will include, but are not limited to: Own end-to-end chip-level static timing analysis and sign-off across all checks, modes, corners, and voltage and temperature conditions. Develop, maintain, and validate sign-off quality Synopsys Design Constraints (SDC) for clocks, resets, high-bandwidth memory (HBM) interfaces, design for test (DFT), and configuration logic.

Adobe is seeking a Machine Learning Engineer to join the Adobe Risk Platform (ARP) team. ARP is Adobe's centralized, adaptive system for detecting, preventing, and mitigating fraud and abuse across products and services — protecting surfaces like Commerce, Stock, and Firefly with real-time risk decisions, without degrading the customer experience. In this position, you will help build and develop machine learning models to identify fraudulent activity, detect abusive account behavior, and protect the experience of hundreds of millions of users. You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team. Key Responsibilities Help build and train ML models covering various fraud and abuse areas. These include financial transaction fraud, device-related deception, and account and identity abuse. The goal is a unified, continuously-updated trust and risk score. Contribute to feature engineering across transaction, device, and behavioral event data. Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs. Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability. Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams to understand fraud and abuse patterns across Adobe's surfaces. Stay ahead of advances in ML/AI, particularly in fraud detection and behavioral modeling, and bring relevant ideas to the team. Minimum Qualifications Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience). 3

Adobe is seeking a Machine Learning Engineer to join the Adobe Risk Platform (ARP) team. ARP is Adobe's centralized, adaptive system for detecting, preventing, and mitigating fraud and abuse across products and services — protecting surfaces like Commerce, Stock, and Firefly with real-time risk decisions, without degrading the customer experience. In this position, you will help build and develop machine learning models to identify fraudulent activity, detect abusive account behavior, and protect the experience of hundreds of millions of users. You'll work across the model lifecycle from raw behavioral data and feature engineering, to model training, deployment, and monitoring alongside senior engineers on the team. Key Responsibilities Help build and train ML models covering various fraud and abuse areas. These include financial transaction fraud, device-related deception, and account and identity abuse. The goal is a unified, continuously-updated trust and risk score. Contribute to feature engineering across transaction, device, and behavioral event data. Build and maintain feature pipelines on Databricks and Spark, transforming raw transaction and device event data into high-quality model inputs. Help translate prototypes into production ML systems, working with senior engineers on scalability, reliability, and observability. Support MLOps practices: experiment tracking, model versioning, CI/CD, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams to understand fraud and abuse patterns across Adobe's surfaces. Stay ahead of advances in ML/AI, particularly in fraud detection and behavioral modeling, and bring relevant ideas to the team. Minimum Qualifications Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field (or equivalent experience). 5

Req ID: FEQ327R409 The team The Fungible team is the “rapid-response squad” within the Field Engineering organisation that engages with customers on the most strategic, highest-potential opportunities across Benelux and the Nordics to accelerate critical use cases, land technical wins, and drive successful Databricks adoption. If you enjoy working on novel use cases across a variety of industries on highly visible engagements, this is the right home for you! The role As a Fungible Solutions Architect, you lead the technical strategy on time-boxed, targeted engagements - typically one to five months - aimed at accelerating a specific set of critical customer workloads from evaluation to a production-grade technical win. You own the architecture conversation, drive platform adoption, and act as a trusted advisor to customer architects and engineering leaders, then transition the momentum you've built to the core account team. You bring technical depth and the judgment to apply it fast, in situations that require strong ownership and are highly visible . Where a specialisation helps you contribute quickly, great — but on this team, breadth, adaptability, and a bias for impact matter just as much as your area of depth. The impact you will have Accelerate what matters most: parachute into strategic, high-profile opportunities and own a clearly defined technical area, moving critical workloads and use cases from evaluation toward production and consumption. Lead the architecture: design scalable, production-grade solutions across data engineering, ML/AI, and real-time analytics, and lead the whiteboarding, design reviews, and trade-off decisions with senior customer stakeholders. Win the technical decision : demonstrate Databricks' differentiation through custom-built solutions in competitive, must-win scenarios. Move fast while maintaining the bar: establish momentum quickly in ambiguous situations and compress timelines without cutting corners. Hand off, don't hold on :

Req ID: FEQ327R409 The team The Fungible team is the “rapid-response squad” within the Field Engineering organisation that engages with customers on the most strategic, highest-potential opportunities across Benelux and the Nordics to accelerate critical use cases, land technical wins, and drive successful Databricks adoption. If you enjoy working on novel use cases across a variety of industries on highly visible engagements, this is the right home for you! The role As a Fungible Solutions Architect, you lead the technical strategy on time-boxed, targeted engagements - typically one to five months - aimed at accelerating a specific set of critical customer workloads from evaluation to a production-grade technical win. You own the architecture conversation, drive platform adoption, and act as a trusted advisor to customer architects and engineering leaders, then transition the momentum you've built to the core account team. You bring technical depth and the judgment to apply it fast, in situations that require strong ownership and are highly visible . Where a specialisation helps you contribute quickly, great — but on this team, breadth, adaptability, and a bias for impact matter just as much as your area of depth. The impact you will have Accelerate what matters most: parachute into strategic, high-profile opportunities and own a clearly defined technical area, moving critical workloads and use cases from evaluation toward production and consumption. Lead the architecture: design scalable, production-grade solutions across data engineering, ML/AI, and real-time analytics, and lead the whiteboarding, design reviews, and trade-off decisions with senior customer stakeholders. Win the technical decision : demonstrate Databricks' differentiation through custom-built solutions in competitive, must-win scenarios. Move fast while maintaining the bar: establish momentum quickly in ambiguous situations and compress timelines without cutting corners. Hand off, don't hold on :

FEQ128R34 The Role As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, m

FEQ128R27 As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations

FEQ128R5 Solutions Architect Greenfield Enterprise France The role is based in Paris or within commuting distance of the office. The Role As a Solutions Architect, you will lead the technical strategy for your Greenfield (New Logo) customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability

FEQ128R7 As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)

SpyCloud is on a mission to make the internet a safer place by disrupting the criminal underground. SpyCloud’s solutions thwart cyberattacks and protect more than 4 billion accounts worldwide. Cybersecurity is an exciting, evolving space, and being at the forefront of the fight to disrupt cybercrime makes SpyCloud a special place to work. If you’re driven to align your career with a fantastic mission, look no further! This Data Engineer II role sits on the Engineering team, reporting to the Senior Director of Data Engineering. Your focus will include evolving our data platform using technologies such as Databricks and Spark, building scalable data pipelines, and serving customers through purpose-built data stores including RDS, Elasticsearch, and DynamoDB. This is a hands-on individual contributor role with ownership of complex data engineering initiatives that support the scalability, reliability, and continued evolution of SpyCloud’s data platform. What You'll Do: Design, build, and improve scalable data systems with a focus on performance, and reliability. Use Databricks and Spark to prepare, transform, and serve high-quality data to customers and downstream systems. Build, optimize, and maintain real-time and batch data pipelines using AWS technologies such as Lambda, S3, DynamoDB, ECS, EKS, and Terraform, as well as develop and maintain pipelines within the Databricks ecosystem. Identify and implement improvements to the cost and performance of data ingestion, transformation, and storage workflows. Be available for on-call support to troubleshoot and remediate data pipeline failures outside of standard business hours. Partner with Product Management, SpyCloud Labs, and Engineering teams to understand requirements and develop effective technical solutions. Evaluate and implement modern tooling for data processing, ML/AI data workflows, and observability. Contribute to architectural and technical design decisions and help implement scalable solutions align

The Role As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. You understand the relevance and application of ML & AI within a range of use cases important to existing digital native customers. The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability to achieve pro

The Role As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain. You understand the relevance and application of ML & AI within a range of use cases important to the digital native customers in the Fintech space The Impact You Will Have Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics Serve as a trusted technical advisor to customer architects, engineering leads, and Directors Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs Influence product direction by providing structured feedback on customer requirements and competitive gaps What We Look For 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms Proficient on the Databricks Platform (or demonstrated ability