Research Engineer

• design, develop, and apply advanced engineering and mathematical models
• drive innovative solutions for complex Intel manufacturing and supply chain challenges
• identify and solve highly complex problems across factory performance, production loading, equipment optimization, decision science, and supply and distribution network operations
• build, develop, validate, and deploy mathematically-based decision algorithms, heuristics, optimization models, and simulation tools
• work collaboratively with business units to identify root causes, define strategic and tactical requirements, and implement appropriate business and technical solutions

Operations Research Engineer

• Design and implement behavioral detections and analytic content using DTEX’s proprietary telemetry and data models.
• Build and maintain full-stack applications and internal tools that support intelligence workflows, detection pipelines, and customer-facing features.
• Develop and optimize algorithms for behavioral modeling, anomaly detection, and risk scoring using structured and unstructured data.
• Lead QE efforts for the Intelligence team, including test automation, regression validation, and release readiness for detection content and supporting tools.
• Partner with data scientists, detection engineers, product managers, and customer success teams to translate intelligence needs into scalable solutions.
• Stay current with emerging threats, detection methodologies, and full-stack technologies to continuously improve DTEX’s detection and response capabilities.

Threat Intel Research Engineer

• Design and build data systems that power reliable AI workflows across enterprise environments
• Develop pipelines for collecting, cleaning, transforming, labeling, and evaluating domain-specific data used by AI systems
• Create data quality frameworks that identify coverage gaps, ambiguity, drift, duplication, leakage, and other failure modes
• Build tools and workflows that help teams turn raw customer data into usable context for retrieval, evaluation, reasoning, and execution
• Partner with AI Researchers and AI Engineers to understand how data quality affects system behavior and production outcomes
• Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in areas where real-world data is sparse or noisy
• Analyze customer workflows and datasets to determine what information AI systems need, where that information should come from, and how it should be represented
• Communicate clearly with internal teams and customer stakeholders about data assumptions, limitations, risks, and tradeoffs

Research Engineer, Data

• Design, prototype, and implement agentic AI systems that perform reliably across complex enterprise workflows
• Build compound AI architectures that combine planning, tool use, retrieval, memory, evaluation, orchestration, and execution
• Investigate how agents reason, coordinate, recover from errors, and interact with external systems under real-world constraints
• Develop evaluation frameworks that measure agent behavior, task completion, reliability, robustness, and failure modes
• Create tools and abstractions that make agent behavior easier to observe, debug, test, and improve
• Partner with AI Researchers to explore new agent architectures and with AI Engineers to harden successful approaches for production use
• Integrate agents into customer APIs, applications, data platforms, and operational workflows
• Communicate clearly with internal teams and customer stakeholders about agent capabilities, limitations, tradeoffs, and risks

• Define and enforce quality standards for training data
• Build tooling and workflows to audit supplier-generated datasets, including sampling strategies, validation pipelines (rule-based and model-assisted), and feedback loops
• Determine if and how human-in-the-loop review workflows can be used to optimize QA
• Partner with data vendors to debug quality issues, provide actionable feedback, and improve their data generation processes
• Continuously integrate QA learnings into infrastructure tools and data vendor portal to reduce anomalies, inconsistencies, and edge cases

• Design structured experiments with real controls and statistical rigor
• Build regression test coverage so we know when a global prompt change is breaking things across workflows we didn't expect
• Create a pipeline of validated, high-confidence improvements engineering can pull from instead of building on faith
• Work with the team to prioritize what actually gets shipped based on what the experiments say
• Own prompt design across Mia's agent workflows - multi-turn, voice-first, healthcare context
• Stay current on what's coming out in prompting research, and agent architecture, and bring back ideas worth testing
• Prototype new approaches locally before anything touches production
• Be the person the Product team comes to when they're stuck on a prompting problem
• Work closely with our Product and Engineering teams - understand where Mia is struggling and help decide what's worth experimenting on
• Translate experiment results into clear recommendations people can actually act on
• Build out evaluation templates and frameworks so this doesn't live only in your head

AI Research Engineer – Prompting

Prompting & AI Agent Research Engineer

• Design structured experiments with real controls and statistical rigor
• Build regression test coverage to know when a global prompt change is breaking things across workflows
• Create a pipeline of validated, high-confidence improvements for engineering
• Work with the team to prioritize what gets shipped based on experiment results
• Own prompt design across Mia's agent workflows
• Stay current on prompting research, bring back ideas worth testing
• Prototype new approaches locally
• Collaborate with Product and Engineering teams
• Translate experiment results into clear recommendations
• Build out evaluation templates and frameworks

AI Research Engineer

• Investigation and execution of Engineering Innovation and Management of Change (MoC) projects.
• Screen and evaluate ideas as assigned and generate new ideas from projects or brainstorming
• Working closely with Innovation Tech Leads, Technology Specialists, Technical Services, R&D, and Offering Managers to ensure alignment on technical and business cases for ideas and projects
• Running project teams, including setting up and leading cadence meetings
• Hosting regular project progress meetings with the Business, Tech Leaders, and Specialists
• Utilizing commercial software to develop simulations and generating process deliverables such as material balances, utilities consumption, equipment sizing, and CAPEX estimates
• Performing techno-economic analyses of process modifications, including the assessment of key parameters impacting process profitability, safety, and reliability.

Senior Innovation Engineer

• Develop measurement performance requirements. Select and evaluate new sensors for current and new sensing capabilities.
• Root-cause sensor signal issues from fleet to bench: use fleet telemetry (time-series + metadata) to isolate cohorts and failure signatures, test hypotheses via circuit simulation and benchtop reproduction, drive fixes design solutions, and partner with HW and FW engineering to implement them.
• Design and validate measurement chain changes to improve physical phenomena observability.
• Downsize on-device data. Develop signal compression techniques, selective data storage decisions, and sampling rate reduction strategies.
• Develop and own test methods to characterize and validate sensor performance.
• Develop hardware-in-the-loop test infrastructure to reproduce the real-world physical phenomena Gridware technology detects. Run hardware-in-the-loop tests to validate changes to our tech stack (HW, phenomena detection algorithms).
• Mentor team members. Raise the technical rigor of experiments, analysis, and validation work.
• Collaborate closely with product managers, data scientists, and SW/HW/FW engineers.

Senior Research Engineer, Electrical

• Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing
• Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)
• Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction
• Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection
• Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions
• Run experiments to validate hypotheses and quantify improvements before production rollout
• Debug failure modes and build error taxonomies across retrieval, reasoning, and generation
• Collaborate with AI and Software Engineers to hand off validated approaches for productionization
• Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product

Applied Research Engineer

• Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML
• Prototype GenAI workflows that map and reason over compliance objects
• Explore ML + probabilistic approaches where GenAI is not the best fit
• Build and maintain evaluation frameworks
• Implement and tune ranking/reranking systems
• Run experiments to validate hypotheses and quantify improvements before production rollout
• Debug failure modes and build error taxonomies across retrieval, reasoning, and generation
• Collaborate with AI and Software Engineers to hand off validated approaches for productionization
• Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling

Senior Applied Research Engineer

• Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, structured retrieval, tool use, and multi-step workflows
• Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements)
• Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and weak supervision
• Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection
• Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions
• Run experiments to validate hypotheses and quantify improvements before production rollout
• Debug failure modes and build error taxonomies across retrieval, reasoning, and generation
• Collaborate with AI and Software Engineers to hand off validated approaches for productionization
• Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product

Staff Applied Research Engineer

• Conduct advanced research in wireless communication systems, including PHY/MAC layers, radio architectures, networking protocols, and end-to-end system design
• Design and evaluate AI/ML-driven wireless algorithms (e.g., semantic communications, intent based and agentic AI communications, GenAI-assisted network optimization, resource allocation, edge intelligence)
• Develop and implement link-level and system-level simulations using tools such as MATLAB, Python, Sionna, or equivalent frameworks
• Build proof-of-concept prototypes and validate concepts on practical platforms or testbeds
• Collaborate with cross-functional research teams across wireless, AI, standards, and prototyping groups

Research Engineer – Wireless, AI/ML

• Extend ontologies and knowledge graph schemas representing claims, evidence, argument structures, defeaters, and confidence
• Implement defeasible argumentation frameworks (e.g., ASPIC+, Dung-style, argumentation schemes) that capture both logical structure and vulnerability to rebuttal
• Operate and quality-control LLM-driven population pipelines, with cross-check scaffolds, provenance tracking, and human-in-the-loop curation
• Architect agent coordination patterns for multi-step research and population tasks, with robust error handling and graceful degradation
• Pre-harden argument structures by mapping the strongest counterarguments, steel-manned objections, and known defeaters
• Build export pipelines that translate structured argumentation into diverse communications formats across audiences and registers
• Maintain current awareness across AI safety, capabilities, and governance sufficient to know when new developments require graph updates, and to know where to find authoritative further detail
• Collaborate with communications staff and researchers to ensure outputs serve real persuasive needs

AI Safety Argumentation Research Engineer

• Lead the technical design and buildout of legal technology pilots and production-ready solutions across practice areas, including Harvey workflows, document automation templates, low-code tools, and custom-developed workflow applications.
• Translate attorney and business requirements into practical technical designs, process maps, data requirements, and implementation plans.
• Build and maintain solutions in approved legal AI, document automation, workflow, and knowledge platforms, including Harvey, Microsoft 365/Copilot or other general-purpose AI tools (ChatGPT, Claude, etc), and other firm-approved systems.
• Partner with custom developers to design and deliver hybrid buy/build solutions, including API integrations, data flows, automation logic, user interfaces, and reporting components.
• Collaborate with product owners to prioritize use cases, define success criteria, and transition pilots into governed, supportable solutions.
• Act as the technical liaison between vendors, internal developers, IT, practice groups, and business teams.
• Provide architecture guidance and hands-on configuration and implementation for key tools and systems, with attention to security, confidentiality, scalability, and maintainability.
• Maintain technical documentation, solution inventories, implementation notes, and reusable design patterns; support knowledge transfer and training.
• Evaluate emerging legal technology and AI capabilities and identify where vendor functionality, firm-built components, or a combined approach can improve attorney workflows.
• Support continuous improvement of attorney- and client-facing workflows through testing, QA, performance tuning, adoption feedback, and process optimization.
• Provide Level 2 support for deployed solutions, including troubleshooting escalated issues, root cause analysis, and coordination with vendors or internal developers for resolution.
• Develop and maintain comprehensive technical documentation, including solution architecture diagrams, configuration guides, user manuals, and runbooks to support ongoing maintenance and future enhancements.

Senior Practice Innovation Engineer

• Deliver mission-critical improvements and new features for our autonomy motion planning and control stack
• Work alongside engineers, research scientists, and domain experts to build optimal and data-driven controls to realize planned vehicle trajectories
• Develop machine-learning vehicle models and learning-based control policies leveraging extensive data from autonomous trucking fleet
• Solve real-world autonomy system challenges by participating in vehicle performance analysis, tuning, and troubleshooting.

Senior Research Engineer, Controls

• Lead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completion
• Build and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experience
• Partner with platform and product engineers to integrate new models into production systems
• Break down ambiguous research ideas into clear, iterative milestones and roadmaps.
• Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineering

Staff Research Engineer, Voice – Speech

• Lead the global community to find, develop, and implement new ideas for Cockpit, Trim, and Displays.
• Ensure creative concepts transition from the lab into production vehicles by coordinating workshops, tracking technologies, and working with cross-functional teams.
• Prioritize a Keep It Simple approach to ensure all design solutions are efficient, practical, and maximize value without over-complication.

Innovation Engineer, Cockpit & Trim

• Research and design custom 3DEXPERIENCE (3DX)/Catia tools using C++ and Python.
• Architect linkage programs to automate data flow between simulation solvers (Hypermesh, LS-DYNA, AutoForm) and CAD environments.
• Ensure developed tools and data pipelines are robust and computationally efficient, minimizing latency and maximizing throughput for large-scale simulation data.
• Lead statistical sensitivity studies and Design of Experiments (DOE) to optimize manufacturing robustness.
• Validate the accuracy and performance of 3DX implementations.
• Partner with Ford subject matter experts in forming, joining, and surface science to develop a unified digital twin for stamping, structural casting, and coating workflows.
• Streamline simulation run-times and automate data processing to enable 100% in-house feasibility validation and rapid design iterations.

See all jobs on JobTailor

Operations Research Engineer

Threat Intel Research Engineer

Research Engineer, Data

Research Engineer

Research Engineer

AI Research Engineer – Prompting

Prompting & AI Agent Research Engineer

AI Research Engineer

Senior Innovation Engineer

Senior Research Engineer, Electrical

Applied Research Engineer

Senior Applied Research Engineer

Staff Applied Research Engineer

Research Engineer – Wireless, AI/ML

AI Safety Argumentation Research Engineer

Senior Practice Innovation Engineer

Senior Research Engineer, Controls

Staff Research Engineer, Voice – Speech

Innovation Engineer, Cockpit & Trim

Research Engineer