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Job Type:
Direct Hire
Remote Status:
Hybrid
Compensation:
$130,000 - $200,000 / yr
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AI Engineer – Machine Learning / LLMs
Location: San Francisco, CA (Hybrid: 3–5 days/week in-office)
Compensation: $130K–$200K
Hiring: 1 role
Visa sponsorship: Available
About the Company
A high-growth AI startup transforming back-office automation for complex business workflows. The company leverages multimodal AI and LLMs to extract, normalize, and link data, enabling more accurate and efficient operations in a traditionally manual industry. The team is small, collaborative, and deeply technical, offering engineers early ownership and influence on product and AI strategy.
Why Join
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High-impact work: Build AI models and features that directly shape business outcomes.
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Technical breadth: Work on ML modeling, infrastructure scaling, AI agent workflows, and backend systems.
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Early-stage influence: Opportunity to define AI strategy, deployment pipelines, and system reliability standards.
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Rapid growth: Join a startup scaling in a complex, high-value industry with strong investor backing.
The Role
As an AI Engineer, you will:
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Design, train, fine-tune, and deploy multimodal LLMs.
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Build and scale AI-driven agent workflows.
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Contribute to ML infrastructure for high-volume training and inference.
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Collaborate cross-functionally with engineering and domain teams to solve practical AI challenges.
Key Responsibilities
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Train, evaluate, and deploy machine learning models.
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Scale ML infrastructure and improve reliability of training/inference pipelines.
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Integrate AI models into production workflows to solve real business problems.
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Develop backend systems to support AI features and automation.
Qualifications
Experience:
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1–3 years in machine learning, ideally with LLMs or multimodal AI (open to new grads from top CS programs).
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Prior startup experience preferred.
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End-to-end experience building practical AI applications (not purely research).
Technical Skills:
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Strong knowledge of fundamental ML algorithms, especially LLMs.
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Experience fine-tuning and deploying LLMs or building agentic systems.
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Production-grade coding skills.
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Experience with cloud platforms (AWS, GCP, Azure).
Soft Skills & Mindset:
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Excellent communicator and collaborative team player.
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Comfortable working in a fast-paced, startup environment.
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Hybrid work-friendly (regular in-office presence expected).
Nice-to-Haves
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Experience with document understanding, data extraction, or workflow automation.
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Familiarity with multimodal AI pipelines or inference optimization.
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