Machine Learning Engineer

ABOUT STYLDOD –

Styldod Inc. is on a mission to democratize home design by building design-led consumer engagement AI. Our innovative platform, 'reimaginehome.ai,' has achieved remarkable success with over 1.5 million registered users in just 12 months, all achieved organically.

We draw insights from a vast repository of real estate data. As a team led by an IIT Delhi alumnus and a National Institute of Design postgraduate, we pride ourselves on being a unique blend of in-house AI experts, AI research collaborators from leading global universities, and design and real estate experts.

At Styldod, we foster a dynamic culture where a small but highly skilled team makes decisive, concentrated bets on solving complex problems that have a profound impact on the world. Our work environment thrives on meritocracy.

Join us if you are passionate about making a significant impact, relish challenging problems, and want to be part of a culture that values excellence, innovation, and a good laugh along the way.

ROLE OVERVIEW –

Machine Learning

KEY RESPONSIBILITIES –

• Develop and optimize deep learning models for image processing, computer vision, and generative AI. 
• Implement, train, and fine-tune models using

  PyTorch

  and related frameworks. 
• Write efficient and clean Python code for model development and data processing. 
• Work with large-scale real estate datasets and build robust data pipelines. 
• Deploy and optimize models for production, ensuring scalability and efficiency. 
• Collaborate with cross-functional teams, including product managers and engineers, to integrate ML models into real-world applications. 
• Stay updated with the latest AI and deep learning research to improve model performance.

REQUIRED SKILLS AND QUALIFICATIONS -

• Strong Python programming

  skills with experience in writing clean, modular, and efficient code. 
• 1-3 years of experience in the domain (Data Science, Machine Learning)

• Deep Learning expertise,

  particularly with

  PyTorch.

   
• Solid understanding of

  computer vision

  techniques (e.g., image segmentation, object detection, generative models). 
• Experience with

  data preprocessing, augmentation, and handling large scale datasets.

   
• Basic knowledge of

  mathematical foundations

  behind ML (e.g., linear algebra, probability, calculus).



GOOD TO HAVE SKILLS –

• Basic knowledge of Transformers and its Derivatives. 
• Experience with HuggingFace Ecosystem (Transformers, Diffusers etc.) 
• Experience with

  Generative AI models

  (e.g., GANs, VAEs, Diffusion Models). 
• Experience with

  3D Computer Vision

  .
• Experience with

  version control (Git), cloud services (AWS/GCP), and SQL/NoSQL databases.