Gruve Visa Sponsorship Jobs USA
Gruve operates in the Science & Research sector and has demonstrated a willingness to sponsor international talent across multiple visa categories, including H-1B visa, E-3 visa, and F-1 OPT. For job seekers who need visa support, Gruve is worth targeting, particularly those in technical and research-oriented roles.
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Get Access To All JobsAbout Gruve
Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.
About The Role
We're seeking an exceptional Senior Engineering Leader to build and lead a high-performing engineering team focused on design and development of a distributed multi-tenant AI inference SaaS platform. Platform development responsibilities include but are not limited to software design, development and testing for multiple domains such as inference engines (AI/ML, program and compiler analysis), core platform services, and observability. This role sits at the intersection of systems engineering, AI/ML operations, and product development, requiring both deep technical expertise and proven leadership capabilities. As a leader at Gruve, you'll drive the technical vision and execution of critical infrastructure that enables our AI capabilities at scale. You'll work closely with cross-functional partners including research scientists, product managers, and other engineering leaders to deliver robust, performant systems that power our AI products. This position is based in the United States and reports to the SVP of Inferencing and Infrastructure Management.
Key Responsibilities
- Team Leadership & Development: Build, mentor, and scale a world-class engineering team of 10-15+ engineers. Foster a culture of technical excellence, collaboration, and continuous learning. Conduct performance reviews, career development planning, and succession planning.
- Technical Strategy & Architecture: Define and execute the technical roadmap for AI inference infrastructure, AI toolchains, and AI software development. Make critical architectural decisions that balance performance, scalability, maintainability, and cost.
- Compiler Design & Optimization: Lead the development of AI inference systems and optimizations for AI workloads, including graph optimization, kernel fusion, and hardware-specific code generation to maximize inference performance.
- AI Model Development & Deployment: Oversee the end-to-end lifecycle of AI models from development through production deployment, including model fine-tuning, quantization, distillation, and serving infrastructure.
- Inference API & Platform Development: Drive the design and implementation of scalable, low-latency inference APIs and platforms that serve models reliably at production scale with strict SLA requirements.
- Spec-Driven Development: Champion rigorous engineering practices including comprehensive technical specifications, design reviews, and documentation to ensure alignment and quality across complex projects.
- Cross-Functional Collaboration: Partner effectively with research, product, and business stakeholders to translate requirements into technical solutions and communicate progress, trade-offs, and risks clearly.
- Delivery & Execution: Own quarterly planning, roadmap prioritization, and on-time delivery of major initiatives. Establish metrics and KPIs to measure team performance and system health.
Basic Qualifications
- 10-15+ years of software engineering experience with at least 5+ years in engineering leadership roles managing teams of 5+ engineers
- Proven track record of building and scaling high-performing engineering teams in high-growth technology companies
- Deep expertise in systems programming languages (C++, Go, Rust, or similar) and architecture design
- Strong background in AI model design, optimization, or adjacent systems-level programming (LLVM, MLIR, XLA, or similar frameworks)
- Hands-on experience with AI/ML model development, training, and inference systems
- Experience with model fine-tuning techniques and deployment optimization (quantization, pruning, etc.)
- Demonstrated ability to design and build production-grade APIs and distributed systems
- Strong understanding of spec-driven development processes and engineering best practices
- Excellent communication skills with ability to influence across all levels of the organization
- Demonstrated ability to work effectively with teams across multiple time zones
- Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)
Preferred Qualifications
- Master's or PhD in Computer Science, Machine Learning, or related field
- Experience at leading AI/ML companies or research labs (OpenAI, Google DeepMind, Meta AI, Anthropic, etc.)
- Direct experience with modern ML frameworks (PyTorch, JAX, TensorFlow) and their compilation stacks
- Background in GPU programming (CUDA, Triton) and hardware acceleration for ML workloads
- Experience with transformer architectures and large language model (LLM) inference optimization
- Track record of shipping production ML systems serving millions of requests per day
- Contributions to open-source compiler or ML infrastructure projects
- Experience with cloud infrastructure (AWS, GCP, Azure) and containerization/orchestration (Kubernetes, Docker)
Salary Range
$240,000 - $300,000 USD + Benefits
This position is with Gruve and is an on-site role based at the Gruve headquarters in Redwood City, California.
Why Gruve
At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you. Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.
About Gruve
Gruve is an innovative software services startup dedicated to transforming enterprises to AI powerhouses. We specialize in cybersecurity, customer experience, cloud infrastructure, and advanced technologies such as Large Language Models (LLMs). Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.
About The Role
We're seeking an exceptional Senior Engineering Leader to build and lead a high-performing engineering team focused on design and development of a distributed multi-tenant AI inference SaaS platform. Platform development responsibilities include but are not limited to software design, development and testing for multiple domains such as inference engines (AI/ML, program and compiler analysis), core platform services, and observability. This role sits at the intersection of systems engineering, AI/ML operations, and product development, requiring both deep technical expertise and proven leadership capabilities. As a leader at Gruve, you'll drive the technical vision and execution of critical infrastructure that enables our AI capabilities at scale. You'll work closely with cross-functional partners including research scientists, product managers, and other engineering leaders to deliver robust, performant systems that power our AI products. This position is based in the United States and reports to the SVP of Inferencing and Infrastructure Management.
Key Responsibilities
- Team Leadership & Development: Build, mentor, and scale a world-class engineering team of 10-15+ engineers. Foster a culture of technical excellence, collaboration, and continuous learning. Conduct performance reviews, career development planning, and succession planning.
- Technical Strategy & Architecture: Define and execute the technical roadmap for AI inference infrastructure, AI toolchains, and AI software development. Make critical architectural decisions that balance performance, scalability, maintainability, and cost.
- Compiler Design & Optimization: Lead the development of AI inference systems and optimizations for AI workloads, including graph optimization, kernel fusion, and hardware-specific code generation to maximize inference performance.
- AI Model Development & Deployment: Oversee the end-to-end lifecycle of AI models from development through production deployment, including model fine-tuning, quantization, distillation, and serving infrastructure.
- Inference API & Platform Development: Drive the design and implementation of scalable, low-latency inference APIs and platforms that serve models reliably at production scale with strict SLA requirements.
- Spec-Driven Development: Champion rigorous engineering practices including comprehensive technical specifications, design reviews, and documentation to ensure alignment and quality across complex projects.
- Cross-Functional Collaboration: Partner effectively with research, product, and business stakeholders to translate requirements into technical solutions and communicate progress, trade-offs, and risks clearly.
- Delivery & Execution: Own quarterly planning, roadmap prioritization, and on-time delivery of major initiatives. Establish metrics and KPIs to measure team performance and system health.
Basic Qualifications
- 10-15+ years of software engineering experience with at least 5+ years in engineering leadership roles managing teams of 5+ engineers
- Proven track record of building and scaling high-performing engineering teams in high-growth technology companies
- Deep expertise in systems programming languages (C++, Go, Rust, or similar) and architecture design
- Strong background in AI model design, optimization, or adjacent systems-level programming (LLVM, MLIR, XLA, or similar frameworks)
- Hands-on experience with AI/ML model development, training, and inference systems
- Experience with model fine-tuning techniques and deployment optimization (quantization, pruning, etc.)
- Demonstrated ability to design and build production-grade APIs and distributed systems
- Strong understanding of spec-driven development processes and engineering best practices
- Excellent communication skills with ability to influence across all levels of the organization
- Demonstrated ability to work effectively with teams across multiple time zones
- Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)
Preferred Qualifications
- Master's or PhD in Computer Science, Machine Learning, or related field
- Experience at leading AI/ML companies or research labs (OpenAI, Google DeepMind, Meta AI, Anthropic, etc.)
- Direct experience with modern ML frameworks (PyTorch, JAX, TensorFlow) and their compilation stacks
- Background in GPU programming (CUDA, Triton) and hardware acceleration for ML workloads
- Experience with transformer architectures and large language model (LLM) inference optimization
- Track record of shipping production ML systems serving millions of requests per day
- Contributions to open-source compiler or ML infrastructure projects
- Experience with cloud infrastructure (AWS, GCP, Azure) and containerization/orchestration (Kubernetes, Docker)
Salary Range
$240,000 - $300,000 USD + Benefits
This position is with Gruve and is an on-site role based at the Gruve headquarters in Redwood City, California.
Why Gruve
At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you. Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.
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Get Access To All JobsTips for Finding Gruve Visa Sponsorship Jobs USA
Target research and technical roles first
Gruve's Science & Research focus means sponsorship is most common for roles requiring specialized technical expertise. Prioritize applying to positions where your field-specific credentials are a clear match, as these align most closely with Gruve's sponsorship history.
Highlight your specialty occupation credentials
For H-1B or E-3 sponsorship at a Science & Research company like Gruve, demonstrating that your role requires a highly specific degree is critical. Tailor your resume to connect your educational background directly to the technical requirements of the role.
Mention your visa status early in the process
Gruve sponsors across multiple visa categories, so transparency about your status from the first conversation helps recruiters quickly determine the right pathway. Waiting until a late stage creates friction and can slow down an already time-sensitive process.
Find Gruve's open roles on a verified sponsorship platform
Sponsorship policies shift, so it's worth browsing current openings on a platform that tracks real filing history. Migrate Mate surfaces verified sponsors so you can filter by actual sponsorship history and confirm Gruve is actively hiring for your visa type.
Gruve jobs are hiring across the US. Find yours.
Find Gruve JobsFrequently Asked Questions
Does Gruve sponsor H-1B visas?
Yes, Gruve sponsors H-1B visas. As a Science & Research company, Gruve has filed H-1B petitions for roles that qualify as specialty occupations, typically requiring a bachelor's degree or higher in a relevant technical or scientific field. If you're targeting an H-1B sponsorship, focus on roles where your degree directly maps to the job requirements, as that alignment is central to a successful petition.
Which visa types does Gruve sponsor?
Gruve sponsors a broad range of visa types: H-1B, E-3, TN, J-1, F-1 OPT, and F-1 CPT. This range makes Gruve a viable target for candidates at different stages, from students on CPT to experienced professionals seeking H-1B or E-3 sponsorship. Australian citizens, Canadians, and Mexicans in technical roles may find the E-3 and TN pathways particularly relevant.
What types of roles at Gruve are most likely to receive visa sponsorship?
Given Gruve's positioning in the Science & Research sector, sponsorship is most commonly associated with specialized technical and research-oriented roles where a specific academic background is a genuine requirement. Generalist or administrative positions are less likely to meet the specialty occupation threshold needed for H-1B or E-3 sponsorship, so focusing on roles with clear degree requirements improves your chances significantly.
How do I find currently open visa-sponsored roles at Gruve?
The most reliable way to find Gruve's active openings with confirmed sponsorship is through Migrate Mate, which tracks verified sponsors and lets you filter by company, visa type, and industry. Because hiring activity changes frequently, checking a platform that uses real sponsorship filing data gives you a more accurate picture than a general job search. Look for roles in Gruve's technical and research departments, as those are most likely to come with sponsorship support.
How do I approach the application process at Gruve as a visa sponsorship candidate?
Start by confirming the role qualifies as a specialty occupation, then be upfront about your visa status in your initial application or screening call. Gruve sponsors across multiple categories, so recruiters are familiar with the process, but they'll need time to assess the right pathway for your situation. Building your case early, including having your educational credentials and work history clearly documented, keeps the process moving and avoids delays when it matters most.
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