AI Chopping Block, Inc. is hiring: IT Engineer in San Mateo
AI Chopping Block, Inc., San Mateo, CA, United States
The Role:
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting‑edge AI research and practical, real‑world applications. Your work will focus on developing, fine‑tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands‑on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Key Responsibilities:
Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
Application Build: Design, develop, and deploy end‑to‑end AI‑powered applications tailored to customer needs.
Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Minimum Qualifications:
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in a software engineering role, with a strong preference for customer‑facing roles.
Robust coding skills required, preferably with proficiency in Python.
Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
Strong interpersonal and communication skills; ability to thrive in dynamic, cross‑functional teams.
Preferred Qualifications:
Master’s degree in Computer Science, Engineering, or a related technical field.
Experience working in a startup or fast‑paced environment.
Hands‑on experience fine‑tuning machine learning models, including supervised fine‑tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.
Compensation & Benefits:
Total compensation for this role also includes meaningful equity in a fast‑growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
Base Pay Range (Plus Equity): $170,000 – $240,000 USD
Fireworks AI is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
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In Summary: As an Applied Machine Learning Engineer, you will serve as a bridge between cutting‑edge AI research and practical, real‑world applications . Your work will focus on developing, fine‑tuning, and operationalizing machine learning models that drive business value and enhance user experiences . This is a hands‑on engineering role that combines technical expertise with a strong customer focus to deliver scalable AI solutions .
En Español: El papel: Como ingeniero de aprendizaje automático aplicado, usted servirá como un puente vital entre la investigación de vanguardia en IA y las aplicaciones prácticas del mundo real. Su trabajo se centrará en desarrollar, ajustar y operationalizar modelos de machine learning que impulsen el valor empresarial y mejoren las experiencias de los usuarios. Esta es una función de ingeniería práctica que combina la experiencia técnica profunda con un fuerte enfoque en el cliente para ofrecer soluciones AI escalables. Responsabilidades clave: Éxito del Cliente: Colaborar directamente con el equipo GTM (Executivos de Cuentas y Arquitectos de Soluciones) para garantizar la integración fluida y la implementación exitosa de las soluciones ML. Demo / Prueba de Concepto (PoC): Construir y presentar PoCs convincentes que demuestren las capacidades de nuestra tecnología AI. Aplicación Edificar, desarrollar e implementar aplicaciones inteligentes artificiales de extremo a extremo adaptadas a las necesidades del cliente. Características/Errores de la plataforma: Contribuir directamente al equipo interno de ML, incluyendo añadir características y resolver problemas. Nuevo modelo Permite integrar y permitir nuevos modelos de aprendizaje automático en la plataforma o los principios de eficiencia. El salario básico se determina por una serie de factores que incluyen calificaciones individuales, experiencia, habilidades, rendimiento en las entrevistas, datos del mercado y ubicación laboral.
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting‑edge AI research and practical, real‑world applications. Your work will focus on developing, fine‑tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands‑on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Key Responsibilities:
Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
Application Build: Design, develop, and deploy end‑to‑end AI‑powered applications tailored to customer needs.
Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Minimum Qualifications:
Bachelor’s degree in Computer Science, Engineering, or a related technical field.
5+ years of experience in a software engineering role, with a strong preference for customer‑facing roles.
Robust coding skills required, preferably with proficiency in Python.
Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
Strong interpersonal and communication skills; ability to thrive in dynamic, cross‑functional teams.
Preferred Qualifications:
Master’s degree in Computer Science, Engineering, or a related technical field.
Experience working in a startup or fast‑paced environment.
Hands‑on experience fine‑tuning machine learning models, including supervised fine‑tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.
Compensation & Benefits:
Total compensation for this role also includes meaningful equity in a fast‑growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
Base Pay Range (Plus Equity): $170,000 – $240,000 USD
Fireworks AI is an equal‑opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
#J-18808-Ljbffr
In Summary: As an Applied Machine Learning Engineer, you will serve as a bridge between cutting‑edge AI research and practical, real‑world applications . Your work will focus on developing, fine‑tuning, and operationalizing machine learning models that drive business value and enhance user experiences . This is a hands‑on engineering role that combines technical expertise with a strong customer focus to deliver scalable AI solutions .
En Español: El papel: Como ingeniero de aprendizaje automático aplicado, usted servirá como un puente vital entre la investigación de vanguardia en IA y las aplicaciones prácticas del mundo real. Su trabajo se centrará en desarrollar, ajustar y operationalizar modelos de machine learning que impulsen el valor empresarial y mejoren las experiencias de los usuarios. Esta es una función de ingeniería práctica que combina la experiencia técnica profunda con un fuerte enfoque en el cliente para ofrecer soluciones AI escalables. Responsabilidades clave: Éxito del Cliente: Colaborar directamente con el equipo GTM (Executivos de Cuentas y Arquitectos de Soluciones) para garantizar la integración fluida y la implementación exitosa de las soluciones ML. Demo / Prueba de Concepto (PoC): Construir y presentar PoCs convincentes que demuestren las capacidades de nuestra tecnología AI. Aplicación Edificar, desarrollar e implementar aplicaciones inteligentes artificiales de extremo a extremo adaptadas a las necesidades del cliente. Características/Errores de la plataforma: Contribuir directamente al equipo interno de ML, incluyendo añadir características y resolver problemas. Nuevo modelo Permite integrar y permitir nuevos modelos de aprendizaje automático en la plataforma o los principios de eficiencia. El salario básico se determina por una serie de factores que incluyen calificaciones individuales, experiencia, habilidades, rendimiento en las entrevistas, datos del mercado y ubicación laboral.