Research Engineer In Data Jobs

Picture this: an AE walks into the room and introduces you. You do the work to understand the prospect and what it takes to win. You get the deal to a product and technical yes. Then someone else closes it, and the win goes on their record, not yours. Most solutions engineer roles stop at the demo. This one doesn't. The win is yours. At Datalab, solutions engineers are the sales team. The people who know the product best should be the ones asking for the signature and talking price. You'd be one of the first hires on this team, working directly with our leadership team. About Datalab Datalab is an applied research lab in New York. We train our own models to turn documents into data you can verify: scans, dense tables, handwriting, the pages other tools quietly get wrong. Because we own the models, a customer's hard problem becomes a roadmap conversation, not a feature request. Our open source work (Marker, Surya, Chandra) has more than 70,000 GitHub stars. Customers include Anthropic, ElevenLabs, Gamma, Reflection AI, and Legora, along with insurers, financial firms, and healthcare companies. We deploy anywhere from our API to fully air-gapped on-prem. We're a small, founder-led team. You'll have real influence on how we sell and what we build. Day to day You own the deal. Everything below is yours, with the whole team as backup when you want it. Own opportunities from first conversation to signature. Win the technical evaluation: scope the problem, run the proof of concept and design the deployment, whether API, VPC or on-prem. Make the business case to the customer's leadership, not just their engineers. Own pricing and commercial terms. Bring what you learn back to product and engineering, where you'll have real say and sway over what we build. Ideal candidate We care about three things: you're credible with engineers, you can hold your own with a C-suite or other executives, and you can close. We're eager to work with someone who has: Significantly contributed t

AI Engineer - FDE (AI Forward Deployed Engineer) Req ID: CSQ427R333 Preferred locations: Stockholm, Sweden. Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialised customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specialisations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Reporting to: Senior Manager - AI FDE, EMEA The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimisations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate

Req: FEQ227R196 Location: Tokyo, Japan Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.)

AI Engineer - FDE (Forward Deployed Engineer) Req ID: CSQ427R191 Location: London, United Kingdom Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Reporting to: Senior Manager - AI FDE, EMEA The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a qua

As a Senior Security Engineer focused on Datadog’s Cloud SIEM product, you will help shape the future of security operations by transforming real-world security expertise into scalable detection, investigation, and response capabilities. You will develop high-impact threat detection content, improve AI-assisted security workflows, and help defenders identify and respond to threats across cloud-native and enterprise environments. Working closely with Product, Engineering, and Security Research teams, you will influence the evolution of Datadog Security products while advancing detection coverage across emerging technologies and attack surfaces. This role offers the opportunity to contribute to open source initiatives, publish security research, and help define the next generation of agentic security operations capabilities. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Research attacker techniques, defensive strategies, and emerging threats, translating findings into scalable security capabilities that protect customers at cloud scale. Design and improve AI-powered investigation, threat hunting, and response workflows that support Datadog’s agentic SOC capabilities. Own the lifecycle of threat detections and automated security workflows, from research and design through deployment, measurement, and continuous improvement. Develop high-fidelity detection content across cloud platforms, SaaS applications, identity systems, endpoints, networks, and other modern attack surfaces. Partner with Product, Engineering, Security Research, and customers to influence roadmap decisions and improve security outcomes across the platform. Mentor security engineers and drive improvements through automation, tooling, rapid prototyping, and data-driven optimization. Who Yo

As a Senior Security Engineer focused on Datadog’s Cloud SIEM product, you will help shape the future of security operations by transforming real-world security expertise into scalable detection, investigation, and response capabilities. You will develop high-impact threat detection content, improve AI-assisted security workflows, and help defenders identify and respond to threats across cloud-native and enterprise environments. Working closely with Product, Engineering, and Security Research teams, you will influence the evolution of Datadog Security products while advancing detection coverage across emerging technologies and attack surfaces. This role offers the opportunity to contribute to open source initiatives, publish security research, and help define the next generation of agentic security operations capabilities. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Research attacker techniques, defensive strategies, and emerging threats, translating findings into scalable security capabilities that protect customers at cloud scale. Design and improve AI-powered investigation, threat hunting, and response workflows that support Datadog’s agentic SOC capabilities. Own the lifecycle of threat detections and automated security workflows, from research and design through deployment, measurement, and continuous improvement. Develop high-fidelity detection content across cloud platforms, SaaS applications, identity systems, endpoints, networks, and other modern attack surfaces. Partner with Product, Engineering, Security Research, and customers to influence roadmap decisions and improve security outcomes across the platform. Mentor security engineers and drive improvements through automation, tooling, rapid prototyping, and data-driven optimization. Who Yo

RDQ427R351 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 and AI infrastructure platform so our customers can use deep data insights to improve their business. Search plays a foundational role in this mission. Whether through keyword-based retrieval, semantic similarity via vector embeddings, or hybrid approaches that combine both, our Search technologies help customers find, discover, and understand information across massive, complex datasets. These capabilities power everything from Retrieval Augmented Generation (RAG), AI assistants, and recommendation systems to enterprise knowledge management, in-product search, and data exploration. As a Staff Engineer for Search, you’ll play a critical role in building and scaling our next-generation Search product — spanning Vector Search, Keyword Search, and Search Quality. You’ll drive the design and evolution of a highly-performant, cost-efficient, and developer-friendly Search stack that enables customers to build AI applications with accuracy, speed, and scale. Beyond hands-on contributions, you’ll help define the long-term vision, mentor senior engineers, collaborate across teams, and lead strategic efforts that expand the technical and business impact of Search at Databricks. Check out our recent blog post: Decoupled by Design: Billion-Scale AI Search The impact you will have: Drive the architecture and evolution of the Search product, delivering scalable, low-latency, and high-quality retrieval across massive multimodal datasets. Identify and solve challenges in indexing, storage, query execution, and ranking — blending innovations in vector search, keyword search, and hybrid retrieval techniques. Partner with infrastructure, product, and research teams to shape APIs and developer experiences that

AI Engineer – Forward Deployed Engineering (AI FDE) (ALL LEVELS) CSQ327R177 Mission The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Open to remote locations. This role is intended for experienced engineers with demonstrated industry experience designing, building, and deploying production GenAI and LLM applications at scale. It is not intended for internship, new graduate, or entry-level applicants. The impact you will have: Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems Own production rollouts of consumer and internally facing GenAI applications Serve as a trusted technical advisor to customers across a variety of domains Present at conferences such as Data + AI Summit , recognized as a thought leader internally and externally Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy Expertise in deploying production-grade GenAI applications, including evaluation and optimizations Extensive years of hands-on industry data science experience, levera

P-1285 About This Role As a staff software engineer for GenAI inference, you will lead the architecture, development, and optimization of the inference engine that powers Databricks Foundation Model API.. You’ll bridge research advances and production demands, ensuring high throughput, low latency, and robust scaling. Your work will encompass the full GenAI inference stack: kernels, runtimes, orchestration, memory, and integration with frameworks and orchestration systems. What You Will Do Own and drive the architecture, design, and implementation of the inference engine, and collaborate on model-serving stack optimized for large-scale LLMs inference Partner closely with researchers to bring new model architectures or features (sparsity, activation compression, mixture-of-experts) into the engine Lead the end-to-end optimization for latency, throughput, memory efficiency, and hardware utilization across GPUs, and accelerators Define and guide standards to build and maintain instrumentation, profiling, and tracing tooling to uncover bottlenecks and guide optimizations Architect scalable routing, batching, scheduling, memory management, and dynamic loading mechanisms for inference workloads Ensure reliability, reproducibility, and fault tolerance in the inference pipelines, including A/B launches, rollback, and model versioning Collaborate cross-functionally on Integrating with federated, distributed inference infrastructure – orchestrate across nodes, balance load, handle communication overhead Drive cross-team collaboration: with platform engineers, cloud infrastructure, and security/compliance teams Represent the team externally through benchmarks, whitepapers, and open-source contributions What We Look For BS/MS/PhD in Computer Science, or a related field Strong software engineering background (6+ years or equivalent) in performance-critical systems Proven track record of owning complex system components and driving architectural decisions end-to-end Deep understa

P-1592 At Databricks, we are passionate about enabling data and AI teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating medical breakthroughs. We do this by building and running the world's best data and AI infrastructure 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 solve 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. As part of the Unity AI Gateway team, you'll build the control plane that every AI request at Databricks passes through: partner and self-hosted models, agents, coding assistants, and MCP servers. It enforces budgets, routes each request to the right model, and applies guardrails inline. Unity AI Gateway is one of our fastest-growing businesses, moving trillions of tokens per week for thousands of customers. The impact you will have: Build the routing layer that picks the right model for each request across quality, cost, latency, availability, and remaining budget Improve reliability, latency, and efficiency of distributed AI workloads Collaborate with research, platform, infra, and AI/ML teams to deliver seamless end-to-end experiences Shape how developers and data scientists build and interact with AI on Databricks What we look for: 8+ years of experience in backend or infrastructure engineering Strong programming skills in Scala, or Go Experience with distributed systems, high-throughput APIs, or cloud-native infrastructure Familiarity with service-oriented architecture, deployment pipelines, and system observability Strong product and ownership mindset. You care about building the right solution, not just any solution Bonus points for: Experience with real-time serving, AI infrastructure, or GPU orchestration Exposure to platforms like

P-1591 At Databricks, we are passionate about enabling data and AI 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 and AI infrastructure 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 solve 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. As part of the AI Platform team, you’ll build the substrate that powers everything from data apps, AI agents, model training, model serving, and vector search. You’ll be joining a high-agency, high-visibility team operating at the frontier of AI infrastructure — with deep ties to research, product, and real-world enterprise use cases. Databricks Mosaic AI is one of our fastest-growing businesses helping thousands of our customers democratize AI within their organizations. We’re building the infrastructure that powers the next generation of AI. We’re hiring across multiple teams in our AI Engineering org including: The impact you will have: Build infrastructure that powers our flagship offerings like MLflow, AI Gateway, Databricks Apps, Agent Framework, Agent Bricks, and Foundation Model APIs, to state a few. Improve reliability, latency, and efficiency of distributed AI workloads Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences Shape how developers and data scientists build and interact with AI on Databricks What we look for: 5+ years of experience in backend or infrastructure engineering Strong programming skills in Scala, Go, or Python Experience with distributed systems, scalable APIs, or cloud-native infrastructure Familiarity with service-oriented a

Overview: Guidepoint is investing in applied AI across its research platform. We're building conversational AI systems that interact with our global expert network at scale — combining real-time voice, LLM-driven orchestration, and retrieval over large proprietary datasets. You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad ownership, close to product and leadership. This role is hybrid in our Toronto Office What You'll Do: Real-time conversational AI: voice- and chat-based agents with low-latency requirements, built on modern telephony and real-time media infrastructure. LLM orchestration: agentic systems that pursue goals over multi-turn conversations, with hard behavioral guarantees enforced in code — not just prompts. Multi-channel session management: stateful user interactions that move seamlessly across channels. Retrieval and grounding: connecting LLM systems to large internal knowledge assets, with structured data flowing back. Evaluation infrastructure: measuring conversational quality against human baselines and gating rollouts on metrics, not vibes. Own services end-to-end: design, implementation, deployment (Kubernetes/Azure), and operations, including latency-sensitive real-time workloads. Design and tune LLM pipelines: context engineering, structured outputs, model selection, cost/latency tradeoffs across vendors. Build the eval loop and treat quality as a number: define metrics, run experiments, gate releases on them. Integrate third-party AI and voice vendors behind clean abstractions so providers stay swappable. Partner with product and compliance stakeholders to encode domain rules into the system. Set engineering patterns for a growing team: code review, observability, incident habits. What You Have: 6+ years of software engineering, with 2+ years building LLM-powered products in production (not notebooks): orchestratio

About AiDASH AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid. Learn more at www.aidash.com. The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024. Join us in Securing Tomorrow Together! The Role We’re looking for a Staff Engineer to architect and build the services behind new products incubated in our product pods. In this role, you will own back-end architecture for multi-tenant SaaS products from first pilot through production scale, make and defend the language and framework calls for each new product, and design the APIs and tool surfaces that let AI agents work with our data. This is a hands-on role: you will write code, ship pilots, and set the technical bar for the engineers around you. How you’ll make an impact: Architect multi-tenant SaaS and distributed back-end systems that scale with customer and data growth Design PostgreSQL schemas, query patterns, and tenancy isolation models built for performance and security Build well-structured APIs and expose product capabilities as tool surfaces for AI agents using MCP or similar protocols Make a

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Full-Stack Engineer to join our Data Acquisition team to build and optimize the interfaces and tools that power our data infrastructure. Responsibilities: Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards. Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management. Design and implement APIs to facilitate data interactions between internal services and external data sources. Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines. Optimize backend services for performance, scalability, and security in a distributed computing environment. Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices. Deploy and maintain infrastructure using Kubernetes and Infrastructure-as-Code (IaC) methodologies. Analyze system performance, conduct experiments, and improve data workflows to maximize efficiency. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in full-stack development. Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go. Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL). Experience building data-intensive applications that handle large-scale datasets. Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker). Prior experience with web crawling and large-scale data processing is a

About eClinical Solutions eClinical Solutions is transforming clinical development with elluminate®, our Clinical Data Cloud , helping life sciences organizations unify, analyze, and unlock the value of their data faster than ever before. By combining a modern cloud platform with expert data services, we empower smarter decisions across the clinical trial lifecycle—accelerating innovation that ultimately improves patient outcomes. Our engineering teams build enterprise-grade, revenue-generating products at the intersection of cloud, data, analytics, and emerging AI technologies . If you’re excited about building sophisticated software that makes a real-world impact on healthcare, this is the place to do it. You will make an impact: As a Senior Software Engineer, AI Enabled Platforms will be a member of the elluminate product development team. elluminate is a next generation data integration and analytics cloud platform that enables life sciences organizations to optimize the aggregation, standardization, and analysis of their data throughout the clinical development life cycle. You are primarily responsible for the design and development of core modules for the platform and will be involved in all phases of the software development lifecycle such as reviewing functional specifications, design, development, unit testing, code reviews and release management. This role is ideal for an experienced engineer who enjoys hands-on development , mentoring others, and bringing modern capabilities—including AI-assisted and agentic workflows—into production-grade systems . Accelerate your skills and career within a fast-growing company while impacting the future of healthcare. Your day to day: Design, develop, test, and deploy scalable, secure, and highly interactive web applications Own and evolve core platform modules , from concept through release and support Influence application and system architecture with a focus on performance, reliabilit