Machine Learning - Computer Vision

  • Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
  • Full-Time
  • Remote
  • 4,500-5,500 USD / Month

Job Description:

About the Role
Were looking for a Senior Machine Learning Engineer to join a fast-growing startup working at the forefront of AI innovation. Youll be part of a tech-driven environment focused on developing cutting-edge solutions in Deep Learning, Computer Vision, NLP, LLMs, and Recommender Systems. This is a fully remote position for engineers passionate about building state-of-the-art ML solutions the kind of projects others only read about.

What Youll Do

  • Lead end-to-end Machine Learning projects, from research to production.
  • Design and implement advanced AI architectures and solutions.
  • Contribute to research and development in Deep Learning, NLP, and Generative Models.
  • Build and optimize object tracking systems on edge devices.
  • Develop generative models for image and video applications.
  • Explore and apply cutting-edge techniques in NLP and Large Language Models.
  • Recommend and implement best practices, tools, and methodologies.
  • Collaborate with a highly motivated and talented cross-functional team.

What You Bring

  • Proven experience in software development and ML engineering (academic or industry).
  • Strong understanding of machine learning algorithms and statistical modeling.
  • Hands-on experience in Deep Learning (mandatory).
  • Expertise in at least one of the following areas:
    • NLP & LLMs
    • Computer Vision
    • Recommender Systems / Predictive Analytics
  • Strong coding skills in Python and familiarity with modern ML frameworks.
  • Ability to take ownership of projects and drive them to completion.
  • Advanced English communication skills (written and spoken).

Why Join

  • Be part of a thriving, fast-paced startup shaping the future of AI.
  • Work on challenging, high-impact projects with the latest technologies.
  • Collaborate with top-tier professionals passionate about innovation.
  • Access to continuous learning and professional growth opportunities.
  • Potential to participate in onsite work and R&D initiatives.