Machine Learning Research Assistant

Onsite
[
New Delhi
]

About Us

At Binaire, we build multi-modal inference systems and frontier text and image models that power next-generation applications. As a fast-growing tech company, we combine cutting-edge research with product-driven engineering to deliver scalable, AI-powered solutions. Join us as a Machine Learning Intern and contribute to real-world ML systems — from model training to deployment.

About the Role

We are looking for a highly motivated Machine Learning Research Assistant to support research and development in cutting-edge ML/AI projects. You will work closely with researchers and engineers to design experiments, implement models, analyze data, and contribute to innovative solutions.

Key Responsibilities

  • Assist in designing, implementing, and evaluating machine learning models
  • Conduct literature reviews and summarize recent research papers
  • Build and preprocess datasets for training and testing
  • Run experiments and analyze results with statistical rigor
  • Optimize models for performance, scalability, and efficiency
  • Collaborate with cross-functional teams (engineering, product, data)
  • Document methodologies, experiments, and findings clearly
  • Contribute to research papers, reports, or internal documentation

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field
  • Strong understanding of machine learning fundamentals (supervised, unsupervised, deep learning)
  • Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
  • Experience with data analysis tools (NumPy, Pandas, Matplotlib)
  • Familiarity with statistics and experimental design
  • Strong problem-solving and analytical skills

Preferred Qualifications

  • Experience with NLP, computer vision, or reinforcement learning
  • Familiarity with research workflows and academic writing
  • Experience with large-scale datasets and distributed training
  • Knowledge of model optimization techniques (quantization, pruning, distillation)
  • Exposure to modern ML frameworks (e.g., JAX, ONNX, MLX)

Nice to Have

  • Contributions to research papers, GitHub projects, or open-source ML work
  • Experience with cloud platforms (AWS, GCP, Azure)
  • Understanding of MLOps pipelines and deployment

What We Offer

  • Opportunity to work on cutting-edge AI research
  • Mentorship from experienced researchers and engineers
  • Flexible working environment
  • Competitive compensation (if applicable)
  • Exposure to real-world ML applications and product development