AI Engineer

Ca-San Francisco-Full Timemid

Machine Learning EngineerData

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Overview

Benefits: 401(k) Bonus based on performance Training & development Role:- AI EngineerKey Responsibilities Apply AI/ML technologies such as machine learning models, LLMs, embeddings,

Technical Tools

Machine Learning EngineerData

Benefits:

401(k)
Bonus based on performance
Training & development

Role:- AI Engineer
Key Responsibilities

Apply AI/ML technologies such as machine learning models, LLMs, embeddings, and basic agentic or RAG workflows under guidance from senior engineers.
Design, develop, and maintain high quality UI and backend services and applications that support AI driven products and platforms.
Implement and integrate RESTful APIs with a focus on security, scalability, and maintainability.
Collaborate with cross functional teams (engineering, AI/ML, product, and platform) to deliver end to end features.
Write clean, testable code and participate in code reviews to maintain high engineering standards.
Assist in troubleshooting, debugging, and resolving production issues.
Learn and follow best practices for cloud native development, reliability, and observability.
Stay current with emerging trends in AI, machine learning, and software engineering.
Provide post-production support

Required Qualifications (Non Negotiable)

Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
2+ years of experience in software engineering, User Interface, backend development, JavaScript, Angular
Proficiency in Python, Java, or Go.
Translating user experience design into code using Angular, Angular Material, NodeJS, strong fundamental knowledge of Object-oriented JavaScript, SASS, CSS3
Knowledge of advanced JavaScript and browser optimizations
Experience with Spring Framework or Spring Boot a plus
Basic understanding of distributed systems, APIs, and backend service design.
Experience working with relational (SQL) and/or NoSQL databases.
Familiarity with software development best practices: version control, testing, and code reviews.

Preferred / Nice To Have Skills

Exposure to AI/ML concepts, including machine learning pipelines or LLM based systems.
Familiarity with embeddings, vector databases, or retrieval augmented generation (RAG).
Experience deploying services in cloud environments (AWS, Azure, or GCP).
Interest in agentic AI, automation, or developer productivity tooling