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Machine Learning Engineer

AI FundAnguilla, Antigua and Barbuda, Argentina13 days ago
ContractorMid-levelData Science

Job Overview

Date Posted

Posted on 4th August 2025

Expiration Date

Expires on 3rd October 2025

Salary

Negotiable

Job Categories
Machine Learning-EngineerML EngineerApplied Machine-Learning-EngineerSenior Machine-Learning-EngineerML Software-EngineerMachine Learning-Platform-EngineerMachine Learning-Developer

RealAvatar:At RealAvatar we build verified AI Avatars in partnership with Public Figures.

RealAvatar:

At RealAvatar we build verified AI Avatars in partnership with Public Figures. We are the Verified Avatar choice in a world of deepfakes poorly trained chatbots.
Founded by Andrew Ng and his fund AI Fund, and led by Jeff Daniel, RealAvatar is developing quickly in this fast-paced space. Whereas 1st gen chatbot makers like Character.AI and Chai build text/audio chatbots with no visual avatar, RealAvatar builds Visual/Audio/Text Avatars for real-time conversations.

Responsibilities:

  • Partner with technical (ML/AI) and product stakeholders to design an effective multimodal AI platform (audio, video and text generation)
  • Design and implement necessary pipeline components to enable new use cases.
  • Develop components for a multimodal Python pipeline that involves audio, video and text generation in a low latency, streaming regime
  • Collect and analyze datasets stored in various databases (SQL, PostgreSQL and vector datastores such as Pinecone)

Requirements:

  • Minimum of 5 years of relevant work experience
  • Expertise in Data Pipeline Engineering: Skilled in developing and maintaining data pipelines to collect, process, and transform data; perform data manipulation and data analysis
  • Expertise with Model Development Optimization: Adept at creating ML model prototypes (e.g. for classification), LLM workflows (e.g. using LLM agents) and/or performing model evaluation.
  • Experience with Model Deployment Monitoring: Experience in implementing and deploying machine learning models into production, setting up robust monitoring systems to track performance and model drift.
  • Experience with cloud computing (GCP or AWS) and data engineering
  • Formal training in Computer Science or an Engineering discipline (Bachelor’s or Master’s)

You Should Be:

  • Eager to move fast and thrive in a dynamic startup environment and achieve excellence with minimal supervision.
  • Be able to deliver high-quality results with a keen eye for detail
  • Collaborative and willing to support others and enhance the collective team performance
  • Have strong verbal and written communication skills and able to articulate technical concepts to non-technical stakeholders
  • Excited to automate things, including testing and verification of your work.