Job summary
Job post source
This job is directly from Stealth AI Startup
Job overview
The Senior Machine Learning Engineer at Stealth AI Startup will lead the design and deployment of advanced AI infrastructures to enhance cybersecurity solutions using generative and agentic AI technologies.
Responsibilities and impact
The role involves deploying AI models in scalable environments, developing automated pipelines for model training and deployment, optimizing models for real-time inference, collaborating with scientists and engineers, maintaining monitoring systems, integrating models with software ecosystems, managing CI/CD workflows, and supporting multimodal AI system integration.
Compensation and benefits
The position offers highly competitive salaries, equity options, comprehensive health benefits including medical, dental, and vision, wellness stipends, professional development budgets, and access to advanced AI/ML tools.
Experience and skills
Candidates should have strong experience in AI/ML engineering, containerization (Docker, Kubernetes), cloud platforms (Azure, AWS, GCP), model optimization techniques, and familiarity with AI frameworks and databases; cybersecurity experience is preferred but not required.
Career development
The company supports professional growth through mentorship, industry conference access, and opportunities to work on cutting-edge AI projects with global impact.
Work environment and culture
The startup culture is collaborative, fast-paced, values diversity and inclusion, and is led by experienced industry veterans providing top-tier mentorship and strategic direction.
Company information
Stealth AI Startup is a well-funded cybersecurity AI company with $25M seed funding, early success with Fortune 500 clients, and leadership with extensive cybersecurity industry experience and successful entrepreneurial history.
Team overview
The candidate will join a world-class leadership team including Heads of AI, Engineering, and Product with experience from top global companies, fostering a dynamic and innovative team environment.
Job location and travel
The job is based in the Silicon Valley Center in North San Jose, CA, offering a collaborative office environment.
Unique job features
The role offers unique opportunities to work with state-of-the-art AI technologies like Large Language Models, Generative AI, and advanced model optimization methods in a startup setting focused on cybersecurity innovation.
Company overview
Stealth AI Startup is a privately-held company based in San Francisco, specializing in advancing Artificial General Intelligence through innovative technology and research. With a team of 11-50 employees, the company operates in stealth mode, maintaining a low profile to avoid public attention while focusing on groundbreaking AI developments. Founded by former FAANG employees and industry experts, the startup recently raised $40 million in funding, highlighting its potential and investor confidence. Key figures include Co-Founder and CTO Gabriel Zaccak and CEO Mohammed Ansari.
How to land this job
Position your resume to highlight your expertise in deploying and optimizing advanced AI models, particularly with containerization tools like Docker and Kubernetes, and cloud platforms such as AWS, Azure, or GCP, as these are critical for the Senior Machine Learning Engineer role at Stealth AI Startup.
Emphasize your experience building end-to-end automated ML pipelines, including model training, fine-tuning (e.g., Q-LoRA, SFT), deployment, and monitoring, showcasing your ability to transition models from research to production seamlessly.
Apply through multiple channels including the Stealth AI Startup’s official corporate website and LinkedIn to maximize your visibility and chances of being noticed by their recruiting team.
Connect with current employees in the AI or engineering divisions at Stealth AI Startup on LinkedIn; start conversations by commenting on recent company news, mentioning shared interests in generative AI or cybersecurity, or asking about their experience working on AI-driven cybersecurity solutions.
Optimize your resume for ATS by incorporating relevant keywords from the job description such as 'Generative AI,' 'containerization,' 'Kubernetes,' 'model deployment,' 'CI/CD for ML,' 'embedding vector databases,' and 'real-time inference' to ensure your resume passes automated filters.
Leverage Jennie Johnson’s Power Apply feature to automate application submissions, tailor your resume for ATS compatibility, identify multiple application portals, and find LinkedIn connections to network with, freeing up your time to prepare for interviews and deepen your AI expertise.
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