Machine Learning Research Engineer

5 days ago


Taguig, National Capital Region, Philippines Phitopolis Full time

Phitopolis is a frontier R&D company focused on developing cutting-edge transformative solutions in computer vision, camera, and sensor data. Our work combines the latest advancements in AI/ML research with real-world applications to redefine the future of intelligent systems.

Job Description

We are seeking a highly skilled Machine Learning Research Engineer to join our elite team. The ideal candidate will be passionate about innovation, enjoy solving complex problems, and thrive in a fast-paced collaborative environment.

Key Responsibilities:

  1. Design and Implement State-of-the-Art Models: Develop and implement state-of-the-art machine learning models, including transformer-based LLMs, GANs, diffusion models, and RNNs (e.g., LSTMs), tailored to computer vision and sensor data.
  2. Predictive Model Development: Develop predictive models for time series analysis from sensor and camera data.
  3. Cutting-Edge Techniques: Explore cutting-edge techniques in generative AI and predictive analytics to solve real-world challenges in computer vision.
  4. Research Publication: Publish research findings internally and integrate them into production-ready solutions.
  5. Data Analysis: Process, clean, and analyze large datasets collected from computer vision systems, cameras, and other sensors.
  6. Innovative Data Representations: Create innovative data representations to enhance the accuracy of generative and predictive models.
  7. Team Collaboration: Work closely with a multidisciplinary team of engineers and researchers to integrate AI models into larger systems.
  8. Mentorship: Provide technical mentorship and guidance to junior engineers.

Qualifications:

Technical Expertise

  1. Transformer-Based Architectures: Proven experience with transformer-based architectures (e.g., GPT, BERT, Vision Transformers).
  2. Generative ML Techniques: Hands-on expertise in generative ML techniques, including GANs, VAEs, and diffusion models.
  3. Predictive Analytics: Proficiency in predictive analytics using LSTMs and advanced time series analysis.
  4. Computer Vision Principles: Solid understanding of computer vision principles and experience with vision datasets.

Programming & Tools

  1. Python and Standard Frameworks: Proficiency in Python and standard machine learning frameworks (PyTorch, TensorFlow).
  2. Libraries and Platforms: Familiarity with libraries like Hugging Face, OpenCV, and NumPy.
  3. Cloud Platforms: Experience with cloud platforms (e.g., AWS, Azure, GCP) for model training and deployment.

Education

  1. Bachelor's or Master's Degree: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, or related fields.
  2. Ph.D. or Published Research: Ph.D. or published research in a relevant domain is a big plus.

Other Skills

  1. Strong Analytical and Problem-Solving Skills.
  2. Excellent Communication Skills.
  3. Ability to Thrive in a Research-Focused Environment.


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