Research Intern - Systems for Reliable and Scalable AI Agents Job at Microsoft Corporation (Redmond)

AI Research Engineer

We are looking for an AI Research Engineer to join the PAIR team and play a cent...

Location

North Macedonia , Skopje

Salary:

Not provided

Hornetsecurity

Expiration Date

Until further notice

Requirements

Applied AI research engineer with at least 3 years of experience in backend development or AI in production
Strong command of Go (microservices, REST/gRPC, high performance) and Python for AI/ML
Solid experience with cloud-native architectures: Docker, Kubernetes, CI/CD, observability, distributed systems, and real-time services
AI/ML/NLP skills: LLMs, embeddings, classification, text generation, model evaluation
Proven ability to design, optimize, and deploy scalable AI services in production
Scientific curiosity, autonomy, rigor, and strong teamwork skills
Excellent communication skills, documentation abilities, and the capacity to simplify complex topics
Professional fluency in English, both written and spoken

Job Responsibility

End-to-End Ownership of AI Solutions: Design, develop, and maintain AI services from prototype to production
Ensure robustness, performance, scalability, and operational reliability of solutions in industrial settings
Rigorous Experimentation & Applied Research: Methodically test and benchmark AI models (standards, metrics, comparisons)
Document results and propose innovative solutions tailored to cybersecurity challenges
Innovation & Technology Watch: Maintain active and structured monitoring of advances in AI/ML, LLMs, agents, NLP, as well as DevOps and MLOps best practices
Anticipate technological developments and contribute to the technical roadmap
Technical Leadership, Documentation & Collaboration: Be a key contributor to technical quality, knowledge sharing, and internal communication
Produce clear documentation and provide technical support to teams

What we offer

Free space for innovation and independent action in a fast-growing international company
Short decision paths and flat hierarchies in an open work atmosphere
Extensive onboarding with a welcome kit, 2-day Onboarding Bootcamp, a Mentoring Program, and regular feedback meetings
Temporary Employee Exchange Program – we provide the ability for you to work at our global office locations and explore the world (e.g. Berlin, Madrid, Malta, Montréal)
Home-office-option (in a hybrid setting) and flexible working time
Team events like Laser Tag, Office Movie Nights, Foodie Fridays and much more
Fit Kit subscription and private insurance for your health
Referral Bonus – 1500€ for each successful referral

Fulltime

AI Research Engineer

We are looking for an AI Research Engineer to join the PAIR team and play a cent...

Location

Germany , Hannover

Salary:

Not provided

Hornetsecurity

Expiration Date

Until further notice

Requirements

Applied AI research engineer with at least 3 years of experience in backend development or AI in production
Strong command of Go (microservices, REST/gRPC, high performance) and Python for AI/ML
Solid experience with cloud-native architectures: Docker, Kubernetes, CI/CD, observability, distributed systems, and real-time services
AI/ML/NLP skills: LLMs, embeddings, classification, text generation, model evaluation
Proven ability to design, optimize, and deploy scalable AI services in production
Scientific curiosity, autonomy, rigor, and strong teamwork skills
Excellent communication skills, documentation abilities, and the capacity to simplify complex topics
Professional fluency in English, both written and spoken

Job Responsibility

Design, develop, and maintain AI services from prototype to production
Ensure robustness, performance, scalability, and operational reliability of solutions in industrial settings
Methodically test and benchmark AI models (standards, metrics, comparisons)
Document results and propose innovative solutions tailored to cybersecurity challenges
Maintain active and structured monitoring of advances in AI/ML, LLMs, agents, NLP, as well as DevOps and MLOps best practices
Anticipate technological developments and contribute to the technical roadmap
Be a key contributor to technical quality, knowledge sharing, and internal communication
Produce clear documentation and provide technical support to teams

What we offer

Hybrid home-office options and flexible, trust-based working hours
Be part of a growing global company in one of the most dynamic industries — cybersecurity
Short decision-making paths and flat hierarchies within an open and collaborative work environment
Opportunities for personal and professional development
Be-Active Bonus — financial support for fitness and sports club memberships
Temporary Employee Exchange Program — opportunities to work at international office locations (e.g. Malta, Madrid, Montreal, Washington, D.C.)
Referral Bonus — €1,500 for each successful referral

AI Research Engineer

We are looking for an AI Research Engineer to join the PAIR team and play a cent...

Location

France , Hem

Salary:

Not provided

Hornetsecurity

Expiration Date

Until further notice

Requirements

Applied AI research engineer with at least 3 years of experience in backend development or AI in production
Strong command of Go (microservices, REST/gRPC, high performance) and Python for AI/ML
Solid experience with cloud-native architectures: Docker, Kubernetes, CI/CD, observability, distributed systems, and real-time services
AI/ML/NLP skills: LLMs, embeddings, classification, text generation, model evaluation
Proven ability to design, optimize, and deploy scalable AI services in production
Scientific curiosity, autonomy, rigor, and strong teamwork skills
Excellent communication skills, documentation abilities, and the capacity to simplify complex topics
Professional fluency in English, both written and spoken

Job Responsibility

Design, develop, and maintain AI services from prototype to production
Ensure robustness, performance, scalability, and operational reliability of solutions in industrial settings
Methodically test and benchmark AI models (standards, metrics, comparisons)
Document results and propose innovative solutions tailored to cybersecurity challenges
Maintain active and structured monitoring of advances in AI/ML, LLMs, agents, NLP, as well as DevOps and MLOps best practices
Anticipate technological developments and contribute to the technical roadmap
Be a key contributor to technical quality, knowledge sharing, and internal communication
Produce clear documentation and provide technical support to teams

What we offer

Flexible hybrid work arrangement
Meal vouchers: €10 per voucher (including €5.92 contribution from Hornetsecurity)
100% coverage of public transportation costs
Health insurance & supplementary pension plan (Axa)
Sports and wellness benefits (subsidy provided)
International exchange program

Fulltime

Principal Technical Program Manager (Quantum Hardware and Firmware Systems)

Microsoft Quantum team is dedicated to developing the first scalable, fault-tole...

Location

United States , Redmond

Salary:

139900.00 - 274800.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree AND 6+ years experience in quantum information, physics, materials science, electrical engineering, hardware systems, engineering, or related technical fields OR equivalent experience
3+ years of experience managing cross-functional and/or cross-team projects.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Citizenship & Citizenship Verification: This role will require access to information that is controlled for export under export control regulations, potentially under the U.S. International Traffic in Arms Regulations or Export Administration Regulations, the EU Dual Use Regulation, and/or other export control regulations. As a condition of employment, the successful candidate will be required to provide proof of citizenship, U.S. permanent residency, or other protected status (e.g., under 8 U.S.C. § 1324b(a)(3)) for assessment of eligibility to access the export-controlled information. To meet this legal requirement, and as a condition of employment, the successful candidate's citizenship will be verified with a valid passport. Lawful permanent residents, refugees, and asylees may verify status using other documents, where applicable.
Ability to leverage AI tools to drive innovation and efficiency (e.g., performance modeling and analysis, research gathering, day to day task automation).
Apply AI to accelerate engineering and lab workflows. Design and build AI agents/copilots that assist with experiment setup, log triage, measurement report generation, protocol templating, and knowledge retrieval (e.g., instrument manuals, design docs).
Evaluate agentic solutions with measurable metrics and humanintheloop safeguards following Microsoft Responsible AI requirements for generative AI.
10+ years of experience owning and managing multi-year, highly complex hardware and firmware product portfolios involving deep-tech or first-of-a-kind technologies, including board bring-up, System-on-Chip (SoC) bring-up, BIOS and driver development, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), quantum systems, advanced chip packaging, cryoelectronics, or other high-reliability hardware.
Experience managing firmware and hardware product development across the full lifecycle, including R&D, system integration, hardware-software integration, new-technology introduction, and technology transfer from R&D into scaled engineering and manufacturing, including hardware quality systems and development or auditing of test and validation protocols.
Experience with hands-on firmware, low-level systems, or advanced hardware R&D, including BIOS, drivers, embedded systems, quantum device development, quantum error correction, measurement/control systems, or similar advanced hardware domains.

Job Responsibility

Drive Program Execution: Lead comprehensive program management for pivotal quantum hardware initiatives. Oversee all phases, including concept development, engineering design, prototyping, validation, operational scaling, and ongoing delivery. Collaborate closely with system architects, research scientists, and hardware engineers to ensure successful outcomes for each project
Strategic Planning & Roadmapping: Work with program management leadership, engineering teams, and executive stakeholders to develop and maintain a clear roadmap for hardware platform advancement. Align technical milestones, allocate resources, manage schedules, and address risks to support Microsoft Quantum’s overarching long-term goals
Cross-Disciplinary Coordination: Facilitate collaboration and alignment among teams specializing in quantum device physics, cryoelectronics, materials science, hardware control, manufacturing, supply chain, integration, and cloud hardware operations. Ensure that integrated efforts result in reliable and scalable hardware solutions
Supplier & Partner Engagement: Manage relationships with external foundries, research laboratories, equipment vendors, and strategic partners. Foster cross-company collaboration, establish clear requirements, and ensure compliance with Microsoft’s standards for quality, safety, and data security
Risk Management: Identify, monitor, and mitigate technical, scheduling, and operational risks throughout program execution. Apply continuous improvement strategies and adjust programs in response to lessons learned and evolving technology trends
Agile Delivery: Oversee Agile program processes and ceremonies, promote transparency by conducting regular reviews and updates, and proactively remove obstacles to ensure timely achievement of critical deliverables
Customer Focus: Incorporate feedback from internal and pilot customers—including researchers, manufacturing partners, and Azure Quantum platform teams—to guide improvements in hardware and processes
Executive Communication: Develop concise, data-driven reports and executive updates that communicate program status, milestones, risks, dependencies, and impact, upholding Microsoft’s high standards for stakeholder engagement and reporting
Embody our culture and values

Fulltime

Senior Quantum Software Engineer - Telemetry (Internet-of-Things & Application)

Microsoft Quantum has assembled a talented and diverse international team to cre...

Location

Netherlands , Delft

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Master's Degree in Computer Science, Software Engineering, Mathematics, Physics, Physical Sciences, or related field AND software industry experience, including developing commercial software, scientific computing applications, or multi-component systems
OR Bachelor's Degree in Computer Science, Software Engineering, Mathematics, Physics, Physical Sciences, or related field AND proven software industry experience, including developing commercial software, scientific computing applications, or
OR equivalent experience.
Demonstarted programming and software engineering experience, including shipping and operating production-quality services or critical internal systems. Strong programming skills in Python (or equivalent), including writing maintainable, testable code
experience with async I/O and concurrency is a plus.
Demonstrated experience in a collaborative environment. Ability to collaborate effectively across disciplines
very strong written and spoken communication, and a documentation-first mindset. Proactive, self-driven execution and comfort working in an evolving, fast-paced research environment.
Hands-on experience designing or implementing telemetry/observability: structured logging, metrics, traces, distributed debugging, and operational runbooks.
Experience building IoT or edge-to-cloud systems, ideally on Azure
familiarity with services such as Azure IoT Hub/IoT Central, Azure Data Explorer, Stream Analytics, or equivalent.

Job Responsibility

Own the end-to-end telemetry design for the quantum machine, spanning IoT telemetry (lab equipment/instrumentation) and application telemetry (measurement, tuning, control, and execution workflows).
Design and implement robust data acquisition from lab instruments and facility equipment used during qubit measurement and control, with attention to reliability, security, and operational safety.
Define telemetry schemas, event taxonomies, and logging standards that enable reproducible diagnostics across experiments, environments, and hardware revisions.
Build and operate scalable pipelines for gathering, buffering, transforming, and shipping telemetry data streams to downstream storage and analytics systems.
Enable human-in-the-loop observability: dashboards, alerts, and automated reports.
Enable machine-in-the-loop observability: provide well-structured data that other software systems and/or AI agents can consume for automated monitoring and feedback loops.
Partner with experimentalists, hardware teams, and control-software developers to translate real debugging needs into well-scoped telemetry features and work items.
Use and help standardize AI-assisted tooling for log analysis, anomaly detection, and troubleshooting automation (where appropriate).
Contribute to software engineering best practices (code reviews, testing, CI/CD, documentation) in a fast-moving R&D environment.
Embody our Culture and Values.

Fulltime

Principal Machine Learning Engineer - Forecasting

We are seeking a Principal Machine Learning Engineer to join the Forecasting tea...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Degree and 12+ years of experience in machine learning engineering, software engineering, data science engineering, or a related quantitative discipline.
10+ years of professional experience building, deploying, and operating production ML, AI, data, or software systems, including significant experience as a technical lead on complex, cross-functional initiatives.
Demonstrated track record of designing or architecting new and existing systems with emphasis on reliability, scale, security, maintainability, and operational excellence.
Deep hands-on experience with the full ML engineering lifecycle, including data pipelines, feature engineering, experimentation, model training, model integration, testing, deployment, monitoring, evaluation, observability, and continuous improvement.
Strong experience deploying forecasting, probabilistic, Bayesian, predictive, NLP, deep learning, or LLM-based systems in production environments.
Experience building or integrating AI systems, including LLM-powered applications, agentic workflows, retrieval or information-retrieval systems, evaluation frameworks, and human-in-the-loop review patterns.
Strong object-oriented programming skills in Python and SQL, with experience using modern ML and software development frameworks such as scikit-learn, PyTorch, TensorFlow/JAX, Spark, Ray, MLflow, Airflow/Prefect/Dagster, FastAPI, or equivalent technologies.
Experience with cloud platforms and distributed systems, including containerization, CI/CD, infrastructure-as-code, model serving, workflow orchestration, batch and streaming data processing, and production support.
Strong software engineering fundamentals, including system design, architecture trade-off analysis, testing strategies, code reviews, source control, build and release processes, performance optimization, and maintainability.
Demonstrated ability to communicate technical strategy, system tradeoffs, and delivery risks to technical and non-technical stakeholders, including senior leaders, product/program owners, scientists, and business partners.

Job Responsibility

Define and drive the technical strategy for enterprise forecasting and AI decision systems, aligning architecture, reusable platforms, and delivery roadmaps to Amgen's planning, supply, commercial, manufacturing, operations, and patient-focused priorities.
Partner with data scientists, product and program leaders, operations, commercial, manufacturing, supply chain, finance, and other business stakeholders to translate ambiguous requirements into shipped software and measurable business outcomes.
Architect, build, and scale production ML, LLM, and agentic AI systems that combine forecasting, predictive analytics, simulation, optimization, and autonomous or semi-autonomous workflow automation.
Productionize advanced statistical, Bayesian, deep learning, and machine learning models, including training, validation, inference, serving, evaluation, lifecycle management, and governed deployment.
Lead development of AI agent components that automate complex forecasting and operational workflows across multiple systems, decision points, datasets, and user groups while preserving appropriate human-in-the-loop review and escalation patterns.
Design secure integrations across enterprise APIs, databases, analytics platforms, workflow systems, cloud services, and AI orchestration patterns to enable multi-system decision support and scalable automation.
Establish robust MLOps and AI engineering capabilities, including model versioning, CI/CD, automated retraining, performance monitoring, observability, drift detection, service-level reliability, rollback strategies, and operational runbooks.
Implement guardrails, model and agent evaluation frameworks, auditability, explainability, responsible AI controls, and human-in-the-loop operating models for production AI systems in high-impact and regulated business contexts.
Research and evaluate state-of-the-art open-source, vendor, and internal tools related to forecasting, LLMs, AI agents, MLOps, model optimization, model serving, and scalable AI infrastructure for potential application to Amgen business problems.
Provide principal-level technical mentorship, design review leadership, and engineering standard-setting across teams, promoting code quality, documentation, reproducibility, testing, security, privacy, maintainability, and operational excellence.

Fulltime

Genai & Competitive Intelligence Engineer

At JFrog, we’re reinventing DevOps to help the world’s greatest companies innova...

Location

Israel , Netanya/Tel Aviv

Salary:

Not provided

JFrog

Expiration Date

Until further notice

Requirements

A proactive builder's mindset: a desire to automate workflows, take end-to-end ownership, and drive continuous improvement
Bachelor's degree or higher in Computer Science, Data Science, Software Engineering, or similar
4+ years of relevant hands-on experience in developing and scaling production-grade GenAI architectures using modern LLM stacks
Proficiency with relevant tools, processes, and frameworks, such as: LangChain, CrewAI, OpenClaw, PyTorch, Keras, NLP, Vector databases, RAG, building MCPs and Skills
Coding fluency in Python and at least one other language (TypeScript/JavaScript, Go or Rust)
Deep understanding of cloud and cloud-native principles, including hands-on experience with major Cloud environments (AWS, GCP, Azure) and containers/Kubernetes
Proven ability to conduct deep technical investigations – analyze complex systems, cloud environments, source code, and documentation, and synthesize the collected data into clear insights
Passion and curiosity to stay current of industry trends and technological advancements
Great communication skills and proven ability to serve as a liaison, coordinating and driving action across diverse org-groups (IS, IT, data science) to ensure effective enterprise-wide systems integration
Excellent English communication (written and verbal)

Job Responsibility

Build, implement, and maintain the AI-powered intelligence stack, using LLMs, agentic capabilities, MCPs, Skills, and advanced RAG, to automate data collection, analysis and sharing
Make knowledge impossible to miss inside JFrog. Build the competitive intel team’s interfaces that get the right competitive insight to the right stakeholder at the right time
Drive projects from concept to execution to delivery
Evaluate and recommend ML and AI tools and frameworks to enhance productivity and effectiveness
Ensure the scalability and reliability of LLM-based system architectures
Engage with requirement gathering and product discussions with internal customers at JFrog
Be the focal point for collaborating with IS, IT and data science teams
Have solid understanding of various aspects of the software development supply chain, including DevOps, DevSecOps and MLOps, and conduct in-depth technical research around them

Fulltime

Automation Engineer, Materials Research Science

Meta Reality Labs is seeking an engineer to advance materials research capabilit...

Location

United States , Redmond

Salary:

184000.00 - 257000.00 USD / Year

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Research Intern - Systems for Reliable and Scalable AI Agents

Job Description

Job Responsibility

Requirements

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