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Mechanized AI

AI Engineer

Job Posted 4 Days Ago Posted 4 Days Ago
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Santiago, Región Metropolitana de Santiago
Senior level
Santiago, Región Metropolitana de Santiago
Senior level
The AI Engineer will enhance ML platforms, design ML systems, implement algorithms, and ensure high-quality client delivery while staying current on AI developments.
The summary above was generated by AI

Title: AI Engineer

Job Type: Full-Time

Location: Remote

Company Description:

Mechanized AI is at the forefront of AI innovation, leveraging cutting-edge technology to

transform legacy systems into modern, efficient, and scalable solutions. We work with

enterprise clients to future-proof their applications, helping them meet the demands of

today’s fast-paced, digital landscape. Our team thrives on solving complex challenges

and delivering AI-driven solutions. We foster a culture of creativity, collaboration, and

continuous learning.

Job Summary:

We are seeking a highly skilled AI Engineer to play a key role in advancing our AI-driven

platform and client solutions.

The ideal candidate has 4+ years of hands-on ML experience beyond academia, thrives

in fast-paced environments, and enjoys solving complex technical challenges. A strong

foundation in cloud-based ML solutions, AI model deployment, and optimization

techniques is essential. Those with a passion for staying at the forefront of AI

advancements and delivering high-impact solutions will excel in this role.

Key Responsibilities:

  • Contribute to building and enhancing our Mechanized AI platform and AI-enabled
  • products including mAI Modernize
  • Serve as ML SME on client projects as needed
  • Design ML systems
  • Research and implement appropriate ML algorithms and tools
  • Select appropriate datasets and data representation methods
  • Run ML tests and experiments
  • Perform statistical analysis and fine-tuning using test results
  • Train and retrain systems when necessary
  • Extend existing ML libraries and frameworks
  • Stay current with emerging technologies and ML best practices to continuously
  • improve our methodologies and tools

Required Skills & Experience:

  • 4+ years of ML experience at a start-up or larger enterprise – high priority
  • 6+ months of experience with Large Language Models (LLMs) and Generative AI
  • (GenAI) applications – high priority
  • Client delivery experience – high priority
  • Effective written and oral communications skills (C1/C2 - advanced/proficient level
  • English is required) – high priority
  • Bachelor’s degree in computer science, software engineering or related field
  • Experience with cloud environments (e.g., AWS, Azure, GCP)
  • Experience with ML frameworks and libraries (TensorFlow, PyTorch, Keras, scikit-
  • learn)
  • Experience developing, deploying, and managing/monitoring models
  • Knowledge of containerization technologies (e.g., Docker, Kubernetes) and
  • microservices architecture
  • Expertise in Object-Oriented Programming (OOP) principles and unit test-driven
  • development methodologies
  • Advanced experience in NLP techniques and applications
  • Strong proficiency in Python programming
  • Familiarity with prompt engineering approaches and best practices
  • Knowledge of data structures, data modeling, and software architecture
  • Strong analytical and problem-solving skills, with ability to propose innovative
  • solutions and troubleshoot issues
  • Ability to work independently and as part of a collaborative team in a fast-paced
  • environment

Preferred Qualifications:

  • Experience in any of the following:
    • Agent development
    • Data privacy
    • Fine tuning LLMs
    • LLM architecture and techniques for performance
    • MLOps
    • ML evaluation
    • Model decay and data drift detection and handling
    • Pulumi, Terraform, and/or Cloud SDKs
    • PySpark
    • Quantization
    • Retrieval-augmented generation (RAG) optimization
    • Security
    • Vector databases

Contact:

Gabriel Martinez

Recruiter

Mechanized AI

Top Skills

AWS
Azure
Docker
GCP
Generative Ai
Keras
Kubernetes
Large Language Models
Machine Learning
Python
PyTorch
Scikit-Learn
TensorFlow

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