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Ai/ml Software Developer
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Head of AI/ML
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AI/ML Lead
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Vice President, Applied AI/ML Lead
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Healthcare AI/ML Architect
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AI/ML Research Scientist
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AI/ML Research Scientist
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Expert AI/ML Scientist
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AI ML Tech Lead
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AI/ML Tech Lead
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AI/ML Engineer
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Applied AI/ML, Sr. Associate
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AI/ML Software Developer
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Senior AI/ML Applied Scientist
1 day ago
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Senior AI/ML Applied Scientist
1 day ago
SAP Palo Alto, United StatesWe help the world run better · Our company culture is focused on helping our employees enable innovation by building breakthroughs together. How? We focus every day on building the foundation for tomorrow and creating a workplace that embraces differences, values flexibility, and ...
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Director of AI/ML Development
1 week ago
Informatica Redwood City, United StatesJob Number: · 37044 · Position Title: · Director, Development · Build Your Career at Informatica · We're looking for a diverse group of collaborators who believe data has the power to improve society. Adventurous, work-from-anywhere minds who value solving some of the world's mos ...
AI/ML Lead - Palo Alto, United States - PetsApp
Description
Company OverviewProphet Security is a force multiplier for security teams.
Prophet AI for Security Operations leverages generative AI technology to streamline the triage, investigation, incident response, and remediation of alerts.
As a result, Prophet reduces manual, tedious, repetitive work for security teams and empowers them to focus their time on higher value security tasks.
We are seeking a talented software engineer to lead our efforts in developing artificial intelligence and machine learning capabilities that drive our product.
Role Summary
As our AI/ML Lead, you'll lead the integration and optimization of large language models (LLMs) and other AI/ML technologies into our product.
Key Responsibilities
LLM Integration & Feature Development : Lead the design and development of innovative features using LLMs, pushing the boundaries of Prophet's capabilities.
Prompt Engineering & Optimization :
Master the art of prompt engineering, fine-tuning, and in-context learning to maximize the potential of LLMs within our product.
Model Evaluation & Benchmarking :
Develop a rigorous model evaluation framework, extending benchmarks like MT-Bench to ensure the robustness and performance of our LLM implementations.
Safety & Guardrails :
Establish comprehensive guardrails for safe and responsible use of LLMs, proactively mitigating potential risks.
Architectural Design :
Shape the architecture of our LLM solutions, making strategic decisions on model configurability, portability, and cost (e.g., one large model vs. multiple task-specific models).
Research & Development :
Stay at the forefront of LLM research, identifying groundbreaking techniques and tools to enhance our product offerings.
Mentorship :
Guide and mentor junior Machine Learning Engineers, sharing your expertise and fostering a culture of innovation.
Required Qualifications
Experience :
Proven track record of successfully shipping LLM-powered products or features.
Technical Expertise :
Deep understanding of LLMs, fine-tuning techniques, prompt engineering, model evaluation, and safety considerations. Proficient in Python.
Research Mind :
Passionate about LLM research, with a demonstrated ability to translate cutting-edge, research concepts into practical applications.
Architectural Thinking :
Experience designing and scaling ML systems, with a keen eye for optimizing performance and resource utilization.
In-depth Prompting Techniques : Familiarity with Chain-of-Thought (CoT), Tree of Thoughts (ToT), ReAct, and other advanced prompting strategies.
Knowledge Synthesis :
Experience with Retrieval-Augmented Generation (RAG) or similar techniques.
Problem-Solving :
Outstanding analytical and problem-solving skills, able to tackle complex challenges in the LLM domain.
Communication & Collaboration :
Excellent communication skills to collaborate effectively with diverse stakeholders and translate technical concepts for non-technical audiences.
Bonus Qualifications
Experience building custom frameworks to streamline LLM interactions (similar to LangChain, LlamaIndex, or Guidance).
Familiarity with agentic architecture concepts and the role of LLMs in enabling agent-based systems.
Publications or Open-Source Contributions related to LLMs.
Experience with Go.
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