Head of AI Engineering at Servian

San Francisco, California, United States

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial Intelligence, IT AutomationIndustries

Requirements

6+ years of experience as an AI / ML focused software engineer
Experience with applied AI development: built new products or systems from the ground up using foundational models
Experience creating and fine-tuning new models, then deploying and refining them in production
Deep appreciation for and commitment to delivering outstanding user experiences
Exceptional communication skills and a proven ability to work cross-functionally
Comfortable with the pace and ambiguity of a fast-growing startup environment
Degree in Computer Science or a related engineering field

Responsibilities

Partner closely with CTO to define and implement the foundational AI / ML architecture for Serval and select key technologies for the platform
Build AI-powered product capabilities and refine them through ongoing evaluation
Be a champion for user experience, incorporating a deep understanding of users to guide design decisions alongside the founding team
Help deliver on the technical and product roadmap
Help establish engineering best practices and standards within the team
Mentor junior engineers and contribute to a culture of technical excellence

Skills

Key technologies and capabilities for this role

AIMLAI ArchitectureMachine LearningSoftware EngineeringApplied AIEngineering Best PracticesMentoring

Questions & Answers

Common questions about this position

Is this role remote or onsite?

This is an onsite position.

What compensation is offered for this role?

The company offers a competitive salary, equity, and benefits.

What are the key requirements for this position?

Candidates need 6+ years of experience as an AI/ML focused software engineer, experience building products from the ground up using foundational models, creating and fine-tuning models for production, a deep appreciation for user experiences, exceptional communication skills, comfort with startup pace and ambiguity, and a degree in Computer Science or related field.

What is the company culture like?

The culture values innovation, ownership, accountability, and fun.

What makes a strong candidate for this Head of AI Engineering role?

Strong candidates have 6+ years in AI/ML engineering with hands-on experience building and deploying models in production, plus early-stage startup experience and familiarity with the tech stack like Go, GRPC, Kubernetes, React, Typescript, AWS, and Terraform.

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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