Help shape the future of AI inference by building platform capabilities that enable developers and enterprises to bring AI applications to life at scale.
Locations (3)
Dallas, Texas, United States
San Francisco, California, United States
New York City, New York, United States
Compensation
Groq is committed to providing competitive compensation through our Total Cash philosophy, which incorporates potential bonus value directly into base pay. The total cash salary range for this position, which is inclusive of the potential bonus value, is $310,400 - $365200, with individual placement determined by your geographic location, experience, skills, and alignment with internal compensation standards. This range is specific to candidates located in the United States. Compensation for international candidates will vary based on local market dynamics. Beyond cash compensation, Groq also offers a Long-Term Incentive (LTI) Program and a robust suite of employee benefits.
Responsibilities
Drive hands‑on product definition and delivery, translating customer needs, technical constraints, and business priorities into detailed specifications, feature requirements, success metrics, and execution plans from concept through launch and continuous improvement.
Bring deep AI infrastructure and cloud platform expertise to complex platform initiatives, contributing to technical specifications, architecture discussions, and roadmap priorities across multiple product workstreams.
Partner closely with Platform Engineering, Distributed Systems, Cloud Infrastructure, Reliability Engineering, Hardware Engineering, and customer‑facing teams to deliver scalable, reliable, and customer‑centric platform capabilities.
Partner with engineering leadership to navigate technical tradeoffs and balance customer impact, technical investments, platform scalability, and long‑term architectural evolution.
Shape customer‑facing cloud capabilities, including inference APIs, developer workflows, and platform experiences, that turn complex infrastructure into services that are easy to adopt, deploy, and scale.
Requirements
Bachelor's degree in Computer Science, Engineering, or related technical field
Lead technical strategy and architecture for AI infrastructure networking at Microsoft.
Compensation
Technical Program Management IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 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 $220,800 - $331,200 per year.
Responsibilities
Define the technical strategy and multi-year AI architecture direction for networking capabilities supporting Microsoft’s large-scale AI training and inference infrastructure
Provide technical leadership across complex AI infrastructure systems spanning GPU and accelerated computing infrastructure, systems software, telemetry, and operations into scalable end-to-end solutions
Translate AI workload requirements into system and networking architecture requirements spanning bandwidth, latency, topology, congestion management, resiliency, security, observability, serviceability, and operational efficiency
Lead technical evaluation and architectural decision-making across technologies including InfiniBand, RDMA, advanced Ethernet fabrics, network interface devices, switches, optics, cables, GPU interconnects, and emerging AI networking technologies
Create clarity in highly ambiguous problem spaces by driving alignment on complex architectural decisions and technical tradeoffs across networking, hardware and software engineering, systems architecture, datacenter infrastructure, operations, supply chain, finance, and customer-facing organizations
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Fullstack Software Engineer
True Talent Solutions Partners · Posted Nov 9, 2026
Lead the development and execution of AI and machine learning strategy for biometric face verification and security.
Compensation
Comp: Negotiable (Base) + Company Performance Bonus (20%) + EMI Share Options + UK iProov Benefits
Responsibilities
Define and steward the AI strategy, roadmap, and vision across core AI research, product, and production domains
Lead teams across research, production/engineering, and MLOps to deliver robust, secure, explainable models for liveness assurance and fraud detection
Oversee model development and deployment pipelines: data ingestion, training, optimization, evaluation, monitoring, and continuous improvement in adversarial biometric threat landscapes
Ensure AI is aligned with product and commercial goals, measuring ROI and outcomes of AI deployments
Drive partnerships and external collaboration with academic, industry, and regulatory stakeholders
Requirements
Master’s or PhD in computer science, machine learning, data science, or a AI related field
The Distinguished Member of Technical Staff (DMTS) for ITP AI is a hands-on technical architect and execution leader in Artificial Intelligence, accountable for turning AI priorities into production-grade solutions to accelerate technology development, silicon design, and engineering execution.
Responsibilities
Partner with SMEs across ITP to understand engineering workflows, data, and constraints, and translate them into scalable, implementable AI architectures.
Define technical designs, solution blueprints, and implementation plans that move AI use cases from concept to production.
Lead hands-on technical execution, including architecture reviews, build decisions, and deployment readiness.
Establish reusable architecture patterns, platforms, and standards that accelerate delivery across ITP.
Translate the ITP AI roadmap into concrete quarterly deliverables with clear milestones, owners, and success criteria.
Requirements
MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, Applied Mathematics, or related field
Distinguished Member of Technical Staff for ITP AI, responsible for architecting and delivering AI solutions across Micron’s Innovation, Technology and Products division.
Responsibilities
Partner with SMEs across ITP to understand engineering workflows, data, and constraints, and translate them into scalable, implementable AI architectures.
Define technical designs, solution blueprints, and implementation plans that move AI use cases from concept to production.
Lead hands‑on technical execution, including architecture reviews, build decisions, integration, and deployment readiness.
Establish reusable architecture patterns, platforms, and standards that accelerate delivery across ITP.
Translate the ITP AI roadmap into concrete quarterly deliverables with clear milestones, owners, and success criteria.
Requirements
MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Engineering, Applied Mathematics, or related field
Nice to have: Publications, patents, open‑source contributions, or industry recognition
Nice to have: Experience applying AI within semiconductor technology, EDA, manufacturing, product development, scientific computing, or high‑performance computing environments
Nice to have: Demonstrated success creating and scaling enterprise AI platforms and capabilities
Nice to have: Experience leading AI transformation efforts within global organizations
Lead Echelon’s infrastructure partnerships and build the business around them, hiring and managing a team, structuring deals, and driving AI data centre capacity projects.
Compensation
A base salary with housing, transport and education allowances, medical cover, and equity through the employee equity programme.
Design and deploy large-scale HPC and GPU infrastructure and architect scalable AI solutions on OCI, serving as a technical advisor for enterprise customers.
Responsibilities
Design and deploy large-scale HPC and GPU infrastructure on Oracle Cloud Infrastructure (OCI)
Architect scalable AI and accelerated computing solutions using Infrastructure as Code (Terraform, Ansible) and Kubernetes.
Develop automated deployment frameworks for cluster provisioning, software installation, and lifecycle management.
Partner with enterprise customers to design solutions that meet AI, machine learning, and high-performance computing requirements.
Design and support Large Language Model (LLM), Agentic AI, and AI platform deployments from proof-of-concept through production.
Requirements
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related technical discipline
Nice to have: Experience with Oracle Cloud Infrastructure (OCI)
Nice to have: Experience with large GPU clusters based on Kubernetes and/or Slurm
Nice to have: Experience supporting AI startups, research organisations, or enterprise AI programmes
Nice to have: Oracle Cloud certifications or equivalent cloud certifications (AWS, Azure, or Google Cloud)
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