Applied AI Engineer at Servian

San Francisco, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, IT AutomationIndustries

Requirements

Experience as a software engineer or machine learning engineer with a focus on applied AI
Proven experience developing and deploying production-grade AI systems, ideally leveraging large language models or foundation models
Experience with prompt engineering, fine-tuning, or evaluation techniques for LLMs
Comfort working with APIs, data pipelines, and cloud environments (AWS, GCP, or similar)
Deep appreciation for delivering high-quality user experiences, not just high-performing models
Excellent communication skills and ability to thrive in a fast-paced, collaborative startup environment
Degree in Computer Science or a related technical field

Responsibilities

Design, build, and deploy AI-powered features from the ground up
Develop and optimize Serval’s applied AI systems — from model selection and fine-tuning to inference and evaluation pipelines
Integrate AI capabilities into production environments, ensuring reliability, scalability, and performance
Collaborate across engineering and product to bring new customer experiences to life
Continuously evaluate model performance and improve results based on data and user feedback
Help establish AI engineering best practices and raise the technical bar across the team

Skills

Key technologies and capabilities for this role

AIMachine LearningModel Fine-tuningInference PipelinesProduction DeploymentLLMSoftware EngineeringScalabilityEvaluation Pipelines

Questions & Answers

Common questions about this position

Is this role remote or onsite?

The position is onsite.

What skills are required for the Applied AI Engineer role?

Required skills include experience as a software or machine learning engineer with a focus on applied AI, proven experience developing and deploying production-grade AI systems using large language models, experience with prompt engineering, fine-tuning, or evaluation techniques for LLMs, comfort with APIs, data pipelines, and cloud environments like AWS or GCP, and excellent communication skills.

What is the salary or compensation for this position?

This information is not specified in the job description.

What is the company culture like at Serval?

Serval has a fast-paced, collaborative startup environment where team members collaborate across engineering and product, continuously improve AI systems based on data and feedback, and establish best practices to raise the technical bar.

What makes a strong candidate for this role?

Strong candidates have experience developing production-grade AI systems with LLMs, including prompt engineering and fine-tuning, comfort with APIs, data pipelines, and cloud environments, plus a deep appreciation for user experiences and startup experience.

Servian

Data analytics and digital solutions provider

About Servian

Servian focuses on data analytics, digital solutions, customer engagement, and cloud services, helping businesses improve decision-making and performance. They build strong data foundations and develop analytics capabilities using machine learning and deep learning to create engaging customer experiences. What sets Servian apart is their customer-centric approach, which emphasizes understanding client needs and leveraging customer data for insights. Their goal is to empower businesses to use data and technology to enhance efficiency and drive innovation.

Sydney, AustraliaHeadquarters

2008Year Founded

ACQUISITIONCompany Stage

Data & Analytics, Consulting, AI & Machine LearningIndustries

501-1,000Employees

Risks

Emerging firms offering similar services at lower costs threaten Servian's market share.

Rapid AI advancements may outpace Servian's integration capabilities.

In-house data analytics development by companies could reduce demand for Servian's services.

Differentiation

Servian specializes in data analytics, digital solutions, and customer engagement.

The company offers end-to-end solutions including data management and cloud infrastructure.

Servian's customer-centric approach prioritizes understanding and meeting client needs.

Upsides

Growing demand for cloud-native data analytics boosts Servian's market potential.

AI-driven customer engagement platforms enhance user experiences and retention rates.

Low-code platforms enable faster deployment, appealing to non-technical users.

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