Responsibilities:

• Design & Release enclosure and structure, cold plate, seals for electric vehicle battery packs
• Manage supply base
• Support all design phase deliverables from initial concept to launch
• Work with supplier manufacturing, STA, and quality teams to ensure design for assembly feasibility
• Develop & maintain quality documents DFMEA, SCCAF, P-diagram, etc.

Requirements:

• B.S. degree in Mechanical Engineering or a related field
• Minimum of 2 years of hands-on experience manufacturing and developing metal components and structure
• Experience in using CAD/CAE tools and ability to optimize tool designs for stamping, welding, and sheet metal, extrusions, castings
• Al, casting, sheet metal joining experience (MIG, SPR, Laser weld, spot welding)
• Excellent teamwork and communication skills
• Self-motivated with the ability to manage multiple tasks
• Proficient computer skills

Preferred:

• M.S. in Mechanical Engineering or complimentary disciplines highly desired
• 5+ years of hands-on experience manufacturing and developing metal components and structure
• One-plus (1+) years engineering experience in battery system design, usage, controls, testing, and system interactions for electrified vehicles
• Record of innovation through invention disclosures, patents, and technical publications
• CAD/CAE capable engineer. Catia, Teamcenter, stack-up tools, fastener health chart, GDT
• PPAP launch experience

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The ideal candidate will have a B.S. degree in Mechanical Engineering or a related field, minimum of 2 years of hands-on experience manufacturing and developing metal components and structure, and experience in using CAD/CAE tools and ability to optimize tool designs for stamping, welding and sheet metal, extrusions, castings.

If you have experience in battery system design, usage, controls, testing, and system interactions for electrified vehicles, record of innovation through invention disclosures, patents, and technical publications, and CAD/CAE capable engineer, Catia, Teamcenter, stack-up tools, fastener health chart, GDT, PPAP launch experience, you will be considered for a Optimal candidate.

This position offers a salary grade 7 -8 and ranges from $86,600 - $166,200. For more information on salary and benefits, please visit: https://fordcareers.co/GSR

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As a Senior Applied Scientist on Bing Places, you will work on challenging problems that require deep technical expertise and a solid focus on real-world impact. You will work end-to-end: from problem formulation and data analysis, through model development and experimentation, to production deployment and live flighting. You will collaborate closely with engineering and product partners to develop, experiment with, and ship models that operate at Microsoft scale, while contributing to the broader scientific community through publications and patents.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Responsibilities:

Formulate complex product and engineering problems as machine learning and AI tasks, and drive them from concept through production.

Design, implement, and evaluate ML-and LLM-based models that improve Bing Places quality, relevance, and coverage.

Conduct rigorous data analysis to understand system behavior, identify opportunities, and define success metrics.

Prototype new modeling approaches and iterate quickly based on offline evaluation and online experimentation.

Own experimentation pipelines, including offline validation and large-scale online A/B flighting.

Partner closely with engineers to integrate models into production systems and ensure long-term reliability and performance.

Drive technical direction within your problem space and influence broader modeling and platform decisions.

Document and communicate results through technical design reviews, papers, and patent filings.

Qualifications:

Required qualifications include a bachelor’s degree in statistics, econometrics, computer science, electrical or computer engineering, or a related field, and 4+ years of related experience, or a master’s degree in a related field and 3+ years of related experience, or a doctorate in a related field and 1+ year of related experience.

Preferred qualifications include a master’s degree in a related field and 6+ years of related experience, or a doctorate in a related field and 3+ years of related experience.

Solid foundation in machine learning, statistical methods, and data-driven problem-solving.

Hands-on experience developing and evaluating models on large-scale, real-world datasets.

Proficiency in Python and experience with modern ML frameworks.

Solid understanding of experimentation methodologies.

Ability to independently scope problems and deliver high-quality solutions in ambiguous environments.

Solid collaboration skills and experience working with engineering and product partners.

Ability to clearly communicate technical concepts and trade-offs to both technical and non-technical audiences.

4+ years of experience applying AI solutions or LLMs to real-world systems.

Background in search, information retrieval, knowledge graphs, or local/entity understanding.

Experience shipping models into large-scale production systems with real user impact.

Track record of publications or granted/pending patents.

Familiarity with distributed training, model optimization, and production ML infrastructure.

Comfort operating across the full lifecycle,from research and prototyping to production and live operations.

#MicrosoftAI Applied Sciences IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 – $258,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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This role is ideal for someone who thrives at the intersection of research and systems engineering: a builder who understands both the math of optimization and the realities of distributed compute.

Responsibilities:

• Design and optimize distributed training infrastructure for large-scale LLMs, focusing on performance, stability, and reproducibility across multi-GPU and multi-node setups.
• Implement and evaluate low-precision numerics (for example, BF16, MXFP8, NVFP4) to improve efficiency without sacrificing model quality.
• Develop kernels and communication primitives that use hardware-level support for mixed and low-precision arithmetic.
• Collaborate with research teams to co-design model architectures and training recipes that align with emerging numeric formats and stability constraints.
• Prototype and benchmark scaling strategies such as data, tensor, and pipeline parallelism that integrate precision-adaptive computation and quantized communication.
• Contribute to the design of our internal orchestration and monitoring systems to ensure that thousands of distributed experiments can run efficiently and reproducibly.
• Publish and share learnings through internal documentation, open-source libraries, or technical reports that advance the field of scalable AI infrastructure.

Skills and Qualifications:

Minimum qualifications:

• Bachelor’s degree or equivalent experience in computer science, electrical engineering, statistics, machine learning, physics, robotics, or similar.
• Understanding of deep learning frameworks (e.g., PyTorch, JAX) and their underlying system architectures.
• Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
• A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.
• Strong engineering skills, ability to contribute performant, maintainable code and debug in complex codebases in areas such as floating-point numerics, low-precision arithmetic, and distributed systems.

Preferred qualifications , we encourage you to apply if you meet some but not all of these:

• Familiarity with distributed frameworks such as PyTorch/XLA, DeepSpeed, Megatron-LM.
• Experience implementing FP8, INT8, or block-floating point (MX) formats and understanding their numerical trade-offs.
• Prior contributions to open-source deep learning infrastructure such as PyTorch, DeepSpeed, or XLA.
• Publications, patents, or projects related to numerical optimization, communication-efficient training, or systems for large models.
• Experience training and supporting large-scale AI models.
• Track record of improving research productivity through infrastructure design or process improvements.

Logistics:

• Location: This role is based in San Francisco, California.
• Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
• Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
• Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

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As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

Key Responsibilities:

• Own the technical vision and architecture for platform security across Anduril's product ecosystem
• Design cryptographic systems, protocols, and key management architectures for autonomous and robotic platforms operating in contested and disconnected environments
• Lead the design of hardware root-of-trust architectures integrating TPMs, TEEs, HSMs, and secure boot across diverse embedded platforms
• Drive the strategy for promoting business-line security implementations into shared, composable platform services
• Serve as the senior technical authority for security architecture reviews across the organization, providing definitive guidance on cryptographic design, protocol security, and system hardening
• Define security patterns, reference architectures, and engineering standards that enable teams across Anduril to build securely and independently
• Mentor and develop senior engineers on the team, raising the bar for security engineering across the organization
• Represent Anduril's security engineering capabilities to customers, partners, and auditors when deep technical credibility is required
• Evaluate emerging threats, cryptographic standards, and security technologies, driving adoption where they strengthen the platform

Required Qualifications:

• 12+ years of experience in software engineering, with significant depth in systems security and cryptography
• Expert-level knowledge of cryptographic protocol design, including key management architectures, certificate systems, and cryptographic agility
• Deep experience with hardware security: TPM, TEE, HSM, secure boot, and hardware root-of-trust design across multiple platform types
• Proficient in two or more of: C++, Rust, Go
• Experience designing security architectures for embedded, real-time, or robotic systems with constrained environments
• Track record of leading cross-organizational technical initiatives and driving architectural decisions that span multiple teams
• Strong ability to communicate complex security concepts to engineering leadership, product teams, and external stakeholders
• Experience performing and leading threat modeling, security architecture reviews, and cryptographic design reviews
• Eligible to obtain and maintain active U.S. Secret security clearance

Preferred Qualifications:

• Experience with post-quantum cryptography, distributed key generation (DKG), or threshold cryptographic schemes
• Background in defense, aerospace, or autonomous systems with exposure to FIPS 140, Common Criteria, or NSA CSfC requirements
• Experience designing secure communication protocols for autonomous platforms or mesh networks
• Deep knowledge of Linux kernel security, mandatory access controls (SELinux/AppArmor), and OS hardening at scale
• Experience building and evolving platform security services consumed by dozens of teams
• Familiarity with compliance frameworks (STIGs, NIST 800-53, CMMC) and translating them into engineering controls that don't compromise developer velocity
• Publications, patents, or recognized contributions in cryptography or systems security
• Experience with Nix build systems and reproducible build pipelines for security-critical software

US Salary Range: $254,000-$336,000 USD

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About this role:

As a Paralegal at Waymark, you will play a vital role in helping Waymark navigate the intersection of law and healthcare technology, ensuring our operations are compliant and efficient, enabling Waymark to transform care to patients with Medicaid benefits. Reporting to the General Counsel, you will help scale our legal infrastructure, becoming a go-to resource for internal teams on routine legal matters and process improvements.

Key Responsibilities:

• Own responsibility for Waymark’s corporate filings, monitor business licensing, patents, trademarks, and registrations; and maintain corporate records
• Maintain, organise and update legal and compliance related documents, templates, policies and procedures
• Operate and implement an agile legal intake process to manage legal requests that reduces friction for internal stakeholders
• Play a role in reviewing vendor contracts, and updating and maintaining contract management system
• Work cross-functionally with other departments to resolve issues and complete substantive tasks with moderate guidance.
• Conduct state and federal regulatory research to support our Medicaid business, develop processes to collect necessary paperwork to ensure compliance, assist with reporting and ad-hoc projects as assigned.

Minimum Qualifications:

• 3+ years of work experience as a paralegal or legal assistant at a law firm or in house legal department.
• Own and drive projects forward independently, demonstrating a strong “get things done” attitude and high attention to detail.
• Exceptional written and verbal communication skills, with a focus on delivering practical solutions.
• Ability to utilise legal technology tools (e.g., GC AI, Lexion (preferred), or other contract management system, Carta).
• Proven ability to manage multiple priorities and deadlines and thrive in a fast-paced environment.
• A strong value for teamwork and the ability to work effectively with diverse teams and perspectives.
• Proficient with healthcare regulatory laws.

Preferred Qualifications:

• Ability to work across a range of legal matters, transactional, regulatory, and compliance.
• Experience in a startup environment.
• Advanced proficiency in automating legal workflows.

Hourly Rate Range:

US Employees in San Francisco/Bay Area: $38.80 - $44.00/hour US Employees in Boston, Los Angeles, Seattle, Washington DC: $35.70 - $40.50/hour US Employees in Arlington, Denver, San Diego, Sacramento: $34.10 - $38.70/hour US Employees in Albany, Atlanta, Austin, Baltimore, Central/Southern Virginia, Charlotte, Chicago, Dallas/Fort Worth, Detroit, Houston, Las Vegas, Miami, Milwaukee, Philadelphia, Portland, Research Triangle, Salt Lake City, Twin Cities: $31.00 - $35.20/hour US Employees in Baton Rouge, Birmingham, Charleston, Cincinnati, Cleveland, Daytona Beach, Indianapolis, Nashville, New Orleans, Omaha, Phoenix, Pittsburgh, St. Louis, Tampa: $30.10 - $34.15/hour

In addition to salary, we offer a comprehensive benefits package. Here’s what you can expect:

• Stock Options: Opportunity to invest in the company’s growth.
• Work-from-Home Stipend: A dedicated stipend for your first year to help set up your home office.
• Medical, Vision, and Dental Coverage: Comprehensive plans to keep you and your family healthy.
• Life Insurance: Basic life insurance to give you peace of mind.
• Paid Time Off: 20 vacation days, accrued over the year, plus 11 paid holidays.
• Parental Leave: 16 weeks of paid leave for birthing parents after six months of employment, and 8 weeks of bonding leave for non-birthing parents.
• Retirement Savings: Access to a 401(k) plan with a company contribution, subject to a vesting schedule.
• Commuter Benefits: Convenient options to support your commute needs.
• Professional Development Stipend: A dedicated stipend supports professional development and growth.

Offer of employment is contingent upon successful completion of a background check.

Don’t check off every box in the requirements listed above? Please apply anyway! Studies have shown that some of us may be less likely to apply to jobs unless we meet every single qualification. Waymark is dedicated to building a supportive, equal opportunity, and accessible workplace that fosters a sense of belonging – so if you’re excited about this role but your past experience doesn’t align perfectly with every preferred qualification in the job description, we encourage you to still consider submitting an application. You may be just the right candidate for this role or another one of our openings!

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Navigation System Architecture & Design:

Establish navigation performance requirements and error budgets for safety-critical applications. Support decomposition of navigation requirements into allocations for sensors, estimation algorithms, and software components. Design detailed software architecture for state estimation implementations, including module interfaces and data flow.

Algorithm Development & Implementation:

Design and implement Extended Kalman Filter algorithms for navigation applications, with broad understanding of state estimation theory and alternative filtering approaches. Implement tightly-coupled and loosely-coupled GNSS/INS integration algorithms. Integrate diverse sensing modalities (vision, RF, celestial etc.) into multi-sensor fusion framework for GPS-degraded environments. Develop fault detection, isolation, and recovery (FDIR) strategies for navigation systems. Implement integrity monitoring and protection level calculations for safety-critical operations.

Certification & Verification:

Develop verification and validation test plans for navigation algorithms. Conduct performance analysis including Monte Carlo simulation, covariance analysis, and flight test data evaluation. Document navigation system design, requirements allocation, and compliance evidence. Support safety assessment activities including failure modes and effects analysis.

Technical Leadership:

Provide technical guidance on navigation architecture and state estimation approaches. Support trade studies evaluating navigation sensor suites and fusion strategies. Mentor junior engineers on state estimation theory and implementation.

Required qualifications:

• MS or PhD in Computer Science, Software Engineering, Electrical Engineering, Aerospace Engineering, Mechanical Engineering, Applied Mathematics, or related field
• 15+ years of experience developing state estimation algorithms for aerospace navigation applications
• Demonstrated experience implementing GNSS/INS integration solutions
• Experience with safety-critical system development and certification processes
• Deep understanding of state estimation theory
• Experience implementing multi-sensor fusion algorithms in production systems
• Strong background in inertial navigation, GNSS positioning, and sensor error modeling
• Strong programming skills in C/C++ and Python/MATLAB for algorithm development and analysis
• Understanding of integrity monitoring, protection levels, and safety assessment methods
• Experience with requirements management and verification/validation processes for certifiable systems
• Understanding of GPS/GNSS signal structure, error sources, and performance characteristics
• Knowledge of IMU error models, calibration, and Allan variance analysis
• Familiarity with alternative navigation sensors (camera, RF ranging, celestial, etc.)
• Understanding of navigation performance metrics (accuracy, integrity, continuity, availability)

Preferred qualifications:

• PhD in relevant field with focus on state estimation or navigation
• Direct involvement in certified navigation system development from requirements through flight test
• Experience with specialized navigation approaches (vision-aided navigation, terrain-referenced navigation, celestial navigation, etc.)
• Publications or patents in navigation or state estimation
• Experience with GPS/GNSS jamming and spoofing mitigation techniques
• Clearance eligible or active security clearance

The salary for this position is $270,000 - $400,000 a year.

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You will work at the intersection of heat transfer, materials science, and optical engineering to push the boundaries of receiver efficiency, durability, and cost-effectiveness.

Key responsibilities include:

• Leading the end-to-end design and development of high-temperature solar receivers optimized for solar field integration
• Developing thermal and optical models to predict receiver performance, including flux distribution, heat transfer efficiency, and thermal stress analysis
• Selecting and qualifying materials capable of withstanding extreme temperatures (800°C–1000°C+), thermal cycling, and high solar flux environments
• Designing receiver geometries (cavity, external, tubular, particle-based) to maximize energy absorption while minimizing thermal losses and mechanical fatigue
• Collaborating with solar collection and controls teams to optimize aiming strategies and flux distribution on receiver surfaces
• Interfacing with heat exchanger and thermal storage engineers to ensure seamless integration of receiver output with downstream systems
• Developing and executing testing protocols for receiver prototypes, including high-flux testing and accelerated life cycle evaluation
• Driving design-for-manufacturing initiatives to reduce receiver cost and improve producibility at scale
• Staying current with advances in receiver technology, high-temperature coatings, and selective absorber materials

Required qualifications include:

• A bachelor's degree in Mechanical Engineering, Aerospace Engineering, Materials Science, or related field; a master's or PhD is preferred
• 7+ years of experience in thermal systems design, with significant focus on high-temperature receiver or heat exchanger development
• Demonstrated expertise in solar thermal receiver design for tower-based or central receiver systems
• Strong background in heat transfer (conduction, convection, radiation), thermodynamics, and fluid mechanics
• Proficiency with thermal simulation tools (ANSYS, COMSOL, SolarPILOT, or equivalent)
• Experience with high-temperature materials including ceramics, refractory metals, and advanced alloys
• Hands-on experience taking receiver designs from concept through prototype testing and into production

Preferred qualifications include:

• Experience with molten salt, liquid sodium, or particle-based heat transfer media
• Knowledge of selective absorber coatings and high-temperature surface treatments
• Familiarity with optical modeling and ray-tracing software for flux analysis
• Background in solar field optimization and aiming point strategies
• Publications or patents in solar thermal receiver technology

Additional information:

• Competitive salary and equity options
• Comprehensive benefits package, including health, dental, and retirement plans
• Dynamic work environment that fosters creativity and innovation
• Opportunities for professional growth and development in a rapidly evolving industry
• Relocation assistance

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Role Summary ------------ As our Patent Attorney, you will be at the heart of our innovation strategy, transforming cutting-edge research into a robust and strategic intellectual property portfolio. You will work closely with our world-class research, engineering, and product teams to protect groundbreaking inventions, shape the future of open-source AI, and support the company's global growth.

Key Responsibilities -----------------

Invention Harvesting

Proactively engage with researchers, engineers, and product managers to identify and prioritize patentable inventions. Advise on what to retain as a trade secret and what to file as a patent application. Draft invention memos based on interviews, internal product documentation, and scientific papers. Translate complex technical ideas into clear, defensible disclosures.

Patent Drafting and Prosecution

Prepare independent claims and manage outside counsel in the drafting and global prosecution of patent applications. Supervise office action responses and ensure consistent, high-quality filings.

Inventor Recognition Program

Administer and evolve internal inventor incentives, including bonuses, awards, and visibility initiatives.

M&A Due Diligence

Support IP due diligence in M&A and strategic investment transactions, including assessment of the IP portfolio, freedom-to-operate risks, and competitive positioning of targets.

Processes and Tools

Develop and maintain internal documentation, workflows, and inventor education on the patent process. Build dashboards to track filings, deadlines, and portfolio metrics. Recommend and manage internal IP tools, databases, and docketing systems. Oversee analytics and reporting dashboards for the IP portfolio.

Portfolio Strategy and Budget Management

Contribute to the development of a global IP strategy aligned with corporate goals. Track and manage IP budget and outside counsel performance.

Open Source and Defensive Alliances

Align patent strategy with Mistral's open source objectives. Evaluate and recommend participation in patent pools, defensive patent networks, or other industry alliances that support open innovation while protecting core assets.

Cross-Functional Collaboration

Partner with other legal team members, product, engineering, and research teams to embed IP thinking in the development lifecycle and broader company strategy.

Ideal Candidate Profile --------------------- You Must Have ...

Patent Expertise

Proven experience drafting patents in complex software/AI domains. Deep understanding of AI patent eligibility (US & Europe). Experience in licensing or litigation (a plus for assessing patent quality).

GenAI Literacy

Hands-on experience with LLMs (e.g., building agents, technical projects). Ability to decode and articulate complex technical concepts (model architectures, training methods). Coding skills (Python, etc.) are a strong plus.

Law Firm Management

Experience selecting, managing, and optimizing external patent firms.

Collaboration with Inventors

Ability to engage with researchers/engineers and extract critical information. Talent for explaining IP concepts to non-legal audiences.

Proactive and Resourceful

Self-driven to anticipate needs, engage stakeholders, and document processes.

In addition, the perfect candidate would have...

Business Acumen

Understanding of how patents drive value for a scale-up.

Open-Source Knowledge

Familiarity with open-source licenses and their intersection with patents.

M&A IP Due Diligence

Experience assessing IP in tech transactions.

Languages Fluent English (required for legal/technical writing). French (a plus for day-to-day collaboration).

Benefits

💰 Competitive cash salary and equity

🥕 Food: Daily lunch vouchers

🥎 Sport: Monthly contribution to a Gympass subscription

🚴 Transportation: Monthly contribution to a mobility pass

🧑‍⚕️ Health: Full health insurance for you and your family

🍼 Parental: Generous parental leave policy

🌎 Visa sponsorship

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About the Team

We build foundational AI infrastructure that enables large-scale training and inference across diverse workloads and rapidly evolving hardware generations. Our work directly shapes how AI systems are designed, deployed, and scaled today and into the future. Engineers on this team operate with end-to-end ownership, deep technical rigor, and a strong bias toward real-world impact.

Microsoft Superintelligence Team

Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!

Responsibilities

Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks. Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements. Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems. Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps. Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations. Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs. Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams. Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.

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We pursue this mission through deep hardware–software co-design, combining rigorous systems thinking with hands-on engineering. The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.

This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.

In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.

Microsoft Superintelligence Team Microsoft Superintelligence team’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

This role is part of Microsoft AI’s Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being. We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact.

Responsibilities Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.

Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.

Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.

Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.

Partner with compiler, kernel, and runtime teams to unlock the full performance of current and next-generation accelerators, including custom kernels, scheduling strategies, and memory optimizations.

Influence and guide AI hardware design at system and silicon levels, including accelerator microarchitecture, interconnect topology, memory hierarchy, and system integration trade-offs.

Lead cross-functional efforts to prototype, validate, and productionize high-impact co-design ideas, working across infrastructure, hardware, and product teams.

Mentor senior engineers and researchers, set technical direction, and raise the overall bar for systems rigor, performance engineering, and co-design thinking across the organization.

Qualifications Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Additional or Preferred Qualifications Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor’s Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Strong background in one or more of the following areas: AI accelerator or GPU architectures Distributed systems and large-scale AI training/inference High-performance computing (HPC) and collective communications ML systems, runtimes, or compilers Performance modeling, benchmarking, and systems analysis Hardware–software co-design for AI workloads Proficiency in systems-level programming (e.g., C/C++, CUDA, Python) and performance-critical software development.

Proven ability to work across organizational boundaries and influence technical decisions involving multiple stakeholders. Experience designing or operating large-scale AI clusters for training or inference. Deep familiarity with LLMs, multimodal models, or recommendation systems, and their systems-level implications. Experience with accelerator interconnects and communication stacks (e.g., NCCL, MPI, RDMA, high-speed Ethernet or InfiniBand). Background in performance modeling and capacity planning for future hardware generations. Prior experience contributing to or leading hardware roadmaps, silicon bring-up, or platform architecture reviews. Publications, patents, or open-source contributions in systems, architecture, or ML systems are a plus.

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