Data Intelligence Systems Engineer Jobs

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering documentati

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. 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. As an AI Reimagination Engineer in Micron's Generative AI Center of Excellence (GenAI COE), you have an outstanding chance to transform how businesses function. You will partner with different business areas to break down large, manual, multi-step processes and redesign them into effective, autonomous systems. This position combines process reimagination with AI systems engineering, making you a key part of the transformation journey. You will collaborate closely with the GenAI COE, IT architecture, security, and project teams. You will lead projects from the initial redesign to the final build, delivering solutions that business teams can adopt and scale. Responsibilities: Decompose end-to-end processes: Map current-state flows, quantify effort and risk, and lead eliminate/simplify/agentify analysis before automation. Architect the agentic solution: Build future-state flows and AI architecture, including task and agent decomposition, orchestration patterns, tool and data access, memory and context strategy, and human-in-the-loop controls. Translate inventions into buildable soluti

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering document

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. As a Product Quality Assurance & Quality Engineering (PQA / PQE) in MTB, you will be responsible for driving product and in-line process quality for Back End manufacturing. This role focuses on establishing effective quality processes and data-driven methodologies to identify, analyze, and mitigate quality risks across assembly, test, and probe operations. You will work closely with Manufacturing, Assembly/Test Engineering, Product Engineering, and Global Quality teams to improve outgoing product quality, manage deviations, support qualification activities, and ensure robust correlation between in-line inspection, probe results, and customer quality requirements, enabling Micron to deliver best-in-class product quality. Additionally, this role will leverage AI, advanced analytics, and digital technologies to transform quality management from reactive issue resolution to predictive and preventive quality intelligence. The role will drive systemic root cause learning, quality knowledge management, and lesson-learned fan-out across both High Volume Manufacturing (HVM) and New Product Introduction (NPI) programs, enabling quality-by-design practices throughout the product lifecycle. Responsibilities and Tasks Drive product and process quality improvement through structured problem solving, data analysis, and continuous improvement initiatives. Leverage AI, advanced analytics, and quality intelligence systems to identify systemic failure modes, accelerate root cause learning,

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. As a Product Quality Assurance & Quality Engineering (PQA / PQE) in MTB, you will be responsible for driving product and in-line process quality for Back End manufacturing. This role focuses on establishing effective quality processes and data-driven methodologies to identify, analyze, and mitigate quality risks across assembly, test, and probe operations. You will work closely with Manufacturing, Assembly/Test Engineering, Product Engineering, and Global Quality teams to improve outgoing product quality, manage deviations, support qualification activities, and ensure robust correlation between in-line inspection, probe results, and customer quality requirements, enabling Micron to deliver best-in-class product quality. Additionally, this role will leverage AI, advanced analytics, and digital technologies to transform quality management from reactive issue resolution to predictive and preventive quality intelligence. The role will drive systemic root cause learning, quality knowledge management, and lesson-learned fan-out across both High Volume Manufacturing (HVM) and New Product Introduction (NPI) programs, enabling quality-by-design practices throughout the product lifecycle. Responsibilities and Tasks Drive product and process quality improvement through structured problem solving, data analysis, and continuous improvement initiatives. Leverage AI, advanced analytics, and quality intelligence systems to identify systemic failure modes, accelerate root cause learning,

eClinical Solutions is a global leader in clinical data intelligence, delivering the elluminate® Clinical Data Cloud® — an AI-powered platform driving agentic data review, SDTM automation, and RBQM for 18 of the top 50 pharmaceutical companies worldwide. As part of our eNOVA AI-First transformation, we are embedding AI across every pillar of clinical development and enterprise operations — compressing cycle times, improving data quality, and redefining how work gets done. As we scale our AI capabilities, we are building a high-impact, hands-on AI engineering function focused on delivering real, production-grade automation across the enterprise. You will make an impact: The Principal AI Engineer – Automation & AI is a hands-on technical leader responsible for designing, building, and deploying AI-powered automation solutions across eClinical Solutions. This role is builder-first (70–80% hands-on development) and operates within a small, high-output team (2–4 engineers). You will work directly with the CTAO and business leaders to identify high-value use cases and rapidly translate them into working AI systems in production. This is not a program management or oversight role. You are expected to build, ship, and iterate continuously, leveraging modern AI tooling and agentic frameworks to deliver measurable impact. Accelerate your skills and career within a fast-growing company while impacting the future of healthcare. Your day to day: Building & Shipping AI Systems Design and deploy agentic AI workflows and automation solutions across enterprise functions including R&D, Engineering, Professional Services, IT, Finance, Sales, and Marketing Build production-grade systems such as: Multi-agent workflows RAG-based applications Document intelligence and summarization pipelines Workflow and process automation solutions Use modern AI tools and frameworks including: Codex, Claude Code, Gemini, NotebookLM LangChain, LangGraph, LlamaIndex (or equivalent

Overview: Qsight is a high-growth division of Guidepoint focused on building data intelligence solutions for the healthcare sector. Qsight leverages proprietary datasets and rigorous analysis of alternative data sources to generate actionable insights for top-tier institutional investors, medical device manufacturers, and pharmaceutical companies. The Qsight team develops market intelligence products designed to be highly relevant, accurate, and scalable – delivering superior insights to a diverse, global client base. We are seeking an experienced, motivated Tehnical Operations Engineer to join our growing team. This is a multiple-hats role focused on SaaS/platform operations and tier-2 support for client-facing systems. You will own the administration and reliability of key tools, troubleshoot and resolve escalations with clear documentation, and build lightweight automation and reporting to reduce manual work as we scale. You will partner closely with Customer Success, Product, and Engineering to proactively monitor, support, and improve critical systems. Through practical, creative problem-solving, you will strengthen reliability, accelerate time to resolution, and increase operational visibility. Day to day, you will triage and resolve client technical questions, manage vendor license administration and renewals, and produce reporting that informs operational decisions. This role is a launchpad toward an SRE/Platform Engineering track as you grow into deeper automation, reliability engineering, and systems design work. This is a hybrid position based out of our Toronto office. What You’ll Do: Platform Support Own routine ops and configuration changes for critical SaaS platforms – Including Tableau, Freshdesk, Datadog, and our own client facing and internal portals Configure and maintain Freshdesk portals, routing, SLAs, permissions, integrations, etc. based on business requirements. Automate manual operations with Python, PowerAutomate, and shell scri

About Scale Scale's mission is to develop reliable AI systems for the world's most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world's most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems is Scale's team focused on pushing the frontier of what agentic applications can do. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale enterprises and governments demand. We're growing fast, with increasing traction across both commercial and public sector customers, and we're just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As Engineering Manager for Agent Oversight, you'll lead the team building our platform for monitoring, evaluating, and improving agentic applications across enterprise and government customers. Agent development tooling is still nascent industry-wide, and we're building the platform to close that gap — covering deployment, monitoring, evaluation, ML-driven improvement, and continuous learning, so agents get better over time. You'll manage the engineering team, drive technical delivery, and work cross-functionally with customers and internal partners to bring these capabilities to production, with the ambition of setting the industry standard for how agentic applications are monitored and improved. Our platform already powers agent deployments for multiple enterprise and government customers. This is a US-based team with members across New York and San Francisco, and yo

About the Team The Fulfillment Planning team builds the intelligence that powers DoorDash’s logistics network. We optimize how deliveries are planned and executed across the full delivery lifecycle, improving customer experience, merchant outcomes, Dasher efficiency, and DoorDash profitability. Our mission is to improve fulfillment quality while reducing fulfillment cost. We do this by applying machine learning, optimization, and systems engineering to the core decisions behind assignment, routing, batching, timing, and fulfillment estimation. The team works on some of DoorDash’s most important logistics systems, including: The core assignment engine that matches deliveries with Dashers in real time. Real-time ETA and fulfillment estimation systems for consumers, Dashers, and merchants across diverse geographies and all business lines. Assignment and planning algorithms for specialized delivery types, including grocery, retail, parcel, and catering. ML models and optimization algorithms that shape demand, improve service quality, and reduce cost. Tier-0 logistics services that require high reliability, low latency, and strong operational discipline. The team also builds reusable ML systems and modeling patterns that scale across DoorDash’s logistics ecosystem. This role will help define the technical direction and best practices for logistics ML at DoorDash. About the Role We’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of large-scale production ML systems that drive real-time decisioning across DoorDash’s fulfillment ecosystem. You will start by owning ML systems for assignment and fulfillment estimation, partnering closely with Product, Data Science, Engineering, and Platform teams to improve delivery quality, cost, and efficiency. Over time, you may also contribute to adjacent areas such as batching, fulfillment execution, demand shaping, and logistics optimization across DoorDash’s business lines. This is

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. Micron's 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. Department Introduction The Probe Area Manufacturing Engineering (AME) team supports semiconductor manufacturing through data-driven decision making, capacity planning, and continuous improvement initiatives. We collaborate closely with Operations, Industrial Engineering, Process Engineering, and Equipment Engineering to improve factory performance and operational excellence. Our team develops scalable systems, analytics, and business processes that enable manufacturing success. Position Overview The Manufacturing Engineering Intern will support projects focused on manufacturing analytics, process optimization, and operational improvement. This role provides hands-on experience applying Industrial Engineering principles within a fast-paced semiconductor manufacturing environment. The successful candidate will partner with engineers to develop insights, improve reporting solutions, and support data-driven decision making. Responsibilities Analyze manufacturing data and develop insights to improve factory performance. Develop dashboards and reporting solutions that support engineering and

Req ID: CSQ327R200 Location: Tokyo, Japan At Databricks, we aim to empower our customers to solve the world's most challenging data problems using the Data Intelligence platform. As a Scale Solution Engineer, you will be critical in advising customers during their onboarding. You will work directly with customers to help them onboard and deploy Databricks in their production environment. The impact you will have: You will ensure new customers have an excellent experience by providing technical assistance early in their journey You will become an expert on the Databricks Platform and guide customers in making the best technical decisions You will work directly with multiple customers concurrently to provide technical solutions. What we look for: Undergraduate degree or higher in Computer Science, Information Systems, or relevant experience 2+ years experience in a technical role, preferably in the data or cloud field Knowledge of at least one of the public cloud platforms AWS, Azure, or GCP is required. Knowledge of a programming language - Python, Scala, or SQL Knowledge of end-to-end data analytics workflow Hands-on professional or academic experience in one or more of the following: Data Engineering technologies (e.g., ETL, DBT, Spark, Airflow) Data Warehousing technologies (e.g., SQL, Stored Procedures, Redshift, Snowflake) Excellent time management and prioritization skills Bonus - Knowledge of Data Science and Machine Learning (e.g., build and deploy ML Models) Excellent written and verbal communication in Japanese and English Excellent time management and prioritization skills Nice to have: Databricks Certification About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices ar

The goal of a Staff Machine Learning Engineer at Scale is to lead the design and deployment of agentic AI systems that operate in real-world, mission-critical government environments. On the Public Sector team, you’ll work at the intersection of agentic ML, systems engineering, and applied research, building foundational infrastructure that enables AI systems to reason, plan, and act reliably at national scale. Our Public Sector ML Team partners directly with U.S. defense and intelligence agencies to deploy AI into classified and regulated environments. Through flagship programs like Donovan and Thunderforge , we are advancing the next generation of agentic AI for geospatial reasoning, planning, and decision support. Staff Machine Learning Engineers play a central role in setting technical direction, owning core architectures, and translating ambitious ideas into production systems trusted by government operators. You will: Lead the architecture and implementation of agentic AI systems, with a focus on long-horizon reasoning, orchestration, and system-level reliability. Build and scale agents that perform complex geospatial reasoning, including interpreting, generating, and reasoning over maps and spatial data. Design and improve retrieval systems across large collections of static and semi-structured documents, enabling agents to surface high-signal context efficiently. Fine-tune and evaluate embedding models to improve recall and precision for mission-critical datasets. Design memory systems that allow agents to persist state, operate over long contexts, and learn from prior interactions. Own and evolve shared agentic infrastructure and core libraries, enabling reuse across teams, products, and Public Sector contracts. Define evaluation strategies for agentic systems, including robustness testing, failure-mode analysis, and regression testing in production environments. Partner closely with engineering managers, product leaders, and researchers to scope high-impac

P-78 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best Data Intelligence Platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The filesystem has emerged as the preferred runtime interface for agentic AI. AI agents use the filesystem for context, memory management, artifact (dashboard, code etc) authoring, version control, sandboxing, and interacting between systems and agents. It is the foundational layer to accelerate AI adoption As a Senior Software Engineer on the Files team, you will innovate at the intersection of storage, performance, and distributed systems, directly shaping our filesystem strategy to power next-generation agentic workloads. The Impact You’ll Have Design, build, and operate the the filesystem platform powering tens of thousands of data, AI and agentic workloads daily Push filesystem performance for the most demanding workloads — profiling and optimizing across the stack, from the API layer down to the Linux kernel Partner with teams across the platform to design and evolve next-generation compute and storage architectures Set the technical direction for how content is organized across Databricks, standardizing around filesystem primitives that apply to every product surface What We’re Looking For Bachelor's degree (or higher) in Computer Science or a related field 5+ years of production-level experience in Java, Scala, C++, Go, Rust, or a similar language 3+ years of experience developing large-scale distributed systems Experience with

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Staff Hardware Engineer to provide advanced operational, diagnostic, and engineering support for Graphcore’s Arm-based hardware platforms across lab and data center environments. This role focuses on supporting hardware bring-up, validation, and troubleshooting of complex AI compute platforms, including server blades, racks, and rack-scale infrastructure. The successful candidate will collaborate closely with engineering, platform, and data center teams to ensure the reliability and performance of next-generation AI systems. The Team The Systems Engineering and Hardware Engineering teams are responsible for enabling the bring-up, validation, and operational reliability of Graphcore’s AI infrastructure platforms. The team works closely with server engineering, firmware teams, platform architects, and data center operations to support the development, testing, and deployment of next-generation AI compute systems. This collaborative environment enables rapid problem-solving and continuous improvement of Graphcore’s hardware platforms from early development through production deployment.