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Stealth Jobs (NOW HIRING)

Stealth Battery Startup

Senior Cell Engineer

San Jose, CA · On-site

$122K - $168K/yr

About the Company We are a stealth-mode battery startup developing cutting-edge battery technology. Our mission is to revolutionize battery technology to accelerate the global transition to clean ...

Stealth Battery Startup

Office Admin/Manager

Fremont, CA · On-site

$39 - $45/hr

About the Company We are a stealth-mode battery startup developing cutting-edge battery technology. Our mission is to revolutionize battery technology to accelerate the global transition to clean ...

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$32.5K

$139.8K

$258K

How much do stealth jobs pay per year?

As of Jul 22, 2026, the average yearly pay for stealth in the United States is $139,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,000.00 and $159,500.00 per year, depending on experience, location, and employer.

What unique challenges might I encounter when joining a company in stealth mode, and how can I best navigate them?

Working at a stealth-mode company often means operating in a highly confidential environment where information is closely guarded, even internally. You may experience limited public recognition for your work and will need to adapt to evolving roles and unclear processes as the product or service develops. Collaboration is key, as teams are usually small and cross-functional, requiring strong communication and flexibility. To thrive, embrace ambiguity, proactively seek clarity from leadership, and be comfortable working with minimal external validation until the company launches publicly.

What is the difference between Stealth vs Security Analyst?

AspectStealthSecurity Analyst
Required CredentialsTypically no formal certifications required, but knowledge of security tools helpsOften requires certifications like CISSP, CompTIA Security+
Work EnvironmentPrimarily in covert operations, often in cybersecurity or military contextsIn office or remote, monitoring and analyzing security threats
Employer & Industry UsageUsed in cybersecurity, military, and intelligence sectorsCommon in corporate, government, and cybersecurity firms
Search & Comparison IntentUnderstanding covert security rolesUnderstanding cybersecurity threat analysis

Stealth roles focus on covert operations within cybersecurity or military contexts, often requiring minimal formal credentials. Security Analysts work openly to monitor and protect systems, often with certifications. Both roles are vital in security but differ in environment and approach.

What are stealth jobs?

Stealth jobs refer to positions at companies or startups that are operating in 'stealth mode.' This means the company is intentionally not publicizing their business model, product, or sometimes even their existence, in order to maintain a competitive edge or privacy during early stages of development. Employees in stealth jobs often work on confidential projects and may be restricted in what they can share publicly. These roles typically require a high degree of trust, discretion, and adaptability. The specifics of the job may only be fully disclosed during the hiring process or after joining the company.
More about Stealth jobs
What cities are hiring for Stealth jobs? Cities with the most Stealth job openings:
What are the most commonly searched types of Stealth jobs? The most popular types of Stealth jobs are:
What states have the most Stealth jobs? States with the most job openings for Stealth jobs include:
What job categories do people searching Stealth jobs look for? The top searched job categories for Stealth jobs are:
Stealth jobs near you
Infographic showing various Stealth job openings in the United States as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, 1% Contract, and 1% Nights. Highlights an 94% Physical, 4% Hybrid, and 2% Remote job distribution, with an average salary of $139,832 per year, or $67.2 per hour.

Head of Inference, Stealth Edge AI Co

Montauk Capital LLC

New York, NY • On-site

Full-time

Posted 17 days ago

Job description

Head of Inference
Full Time, Remote, NYC Preferred (US Based)
About Montauk Capital
Montauk Capital builds and backs companies at the forefront of the Electron Economy, the generational shift towards electrified, intelligent technologies reshaping industries and driving unprecedented demand for energy. Our team combines deep investing acumen with decades of operating experience to give founders the strategic clarity and hands-on support that accelerates the building of enduring companies of consequence.
About Stealth Edge AI Co
Co-founded by Montauk Capital, Stealth Edge AI Co is a pre-seed venture specialized in modular, metro-edge AI capabilities. By leveraging existing infrastructure for inference deployment, Edge AI provides low-latency, SLA-guaranteed performance across diverse GPU SKUs and colocation environments. Our technology intelligently routes traffic based on demand proximity and real-world network limitations, bypassing the heavy power and infrastructure requirements of traditional hyperscalers. Currently initiating operations with pilot nodes in NYC, we are executing a city-by-city expansion strategy with plans for a broader multi-metro rollout.
About the Role
We are seeking a visionary and execution-oriented Head of Inference. You'll define the inference architecture, make foundational decisions, build the first POC, and own this domain end to end alongside the CEO. You will be a senior, hands-on technical leader and the technical authority on inference in the room. You'll own the key technical decisions, and will be the internal and external expert on inference. You will own the core inference capability driving the platform and customer experience, and have a strong voice over the technical foundation of the company. You'll evolve the vision into a viable proof of concept, building the practical system to then design and implement distributed inference systems. Alongside the CEO, you'll represent the company with top-tier partners, early customers and investors, and will own this domain end to end. In addition to the CEO, you will have the support of a team of strong advisors, and the initial founding team.
What You'll Do
  • Create the inference strategy and define the inference architecture for Edge AI
  • Own the inference serving layer end-to-end: vLLM, TensorRT-LLM, Triton, or equivalent
  • Build a credible POC fast - proves the platform works to NVIDIA, cloud providers, and customers
  • Drive cost-per-token optimization
  • Optimize GPU utilization, KV-cache management, and batching for production workloads
  • Own observability and reliability SLAs
  • Build distributed inference pipelines across multi-GPU, multi-node edge deployments
  • Set performance baselines and SLAs for inference latency and throughput, plus observability and performance SLA's
  • Define quantization strategy
  • Translate complex inference requirements for infrastructure designs
  • Define the software access layer architecture and oversee integration efforts
  • Engage credibly with investors, partners, and technical stakeholders, represent the company externally

What You'll Bring
You have a passion for inference and a background as a hands-on technical builder who has directly implemented inference systems before, ideally in production or near-production environments. Deep knowledge and are excited about model serving, and the practical engineering required to make an inference system work on real hardware. You can take a vision and initial concept and translate it into a viable POC quickly and are comfortable making foundational technical decisions quickly, in ambiguity, and building first of a kind.
If inference is your craft and you've built systems in production, we want to talk.
  • Production inference serving - vLLM, TensorRT-LLM, Triton Inference Server, or equivalent distributed at scale
  • Quantization, SGLang, containerization, cost-per-token
  • Observability tooling:distributed tracing, latency profiling, alerting. Instrument and debug complex distributed systems with a focus on building world-class observability and debuggability tools
  • C++/CUDA/Rust
  • GPU utilization and CUDA kernel optimization - has pushed hardware to its limits
  • Batching, KV-cache, speculative decoding expertise
  • Scale systems using Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference
  • Has built a serving system that NVIDIA and cloud providers respect
  • Model deployment and serving
  • Systems engineering
  • Technical leadership experience, either over teams or outcomes
  • Startup / 0→1 DNA: You ship fast and communicate clearly

Why Join Us
  • Category-Defining Opportunity: Solving the AI inference bottleneck without the burden of power and infrastructure constraints Own the metro edge inference across heterogeneous, disparate compute nodes
  • Massive Market Opportunity: AI spending projected to exceed hundreds of billions annually, 54GW of AI Inference demand expected by 2030
  • Studio Support: Leverage Montauk Capital's resources, network, and operational expertise during critical early stages
  • Competitive compensation + equity: True ownership over what you build

Apply