Machine Learning Engineer

About RocketFrog.ai

RocketFrog.ai is an AI Studio for Business, delivering real-world impact through advanced AI solutions. We specialize in Agentic AI, Deep Learning, and full-stack AI-first product development with applications across industries such as Healthcare, Pharma, Banking, Finance, Insurance, and Hi-Tech.

🚀 Ready to take a Rocket Leap with Science?

Role Overview

We are seeking a high-potential Machine Learning Engineer with 2+ years of experience and a strong academic background to join our AI Innovation team. You will design and implement models that drive intelligent automation and AI-first products for enterprise-grade use cases.

Key Responsibilities

• Design, develop, and optimize machine learning models for applications in NLP, Computer Vision, Speech, or multi-modal domains
• Build scalable pipelines for data preprocessing, training, and evaluation
• Propose research-backed approaches for addressing key business challenges.
• Translate academic research and ideas into efficient, production-ready implementations
• Collaborate with product, engineering, and domain teams to align ML systems with business needs
• Stay up-to-date with the latest developments in ML frameworks, tooling, and deployment strategies

Required Skills & Expertise

• Strong knowledge of Linear Algebra, Probability, and Statistics

• Machine Learning Proficiency

  : Hands-on experience with training and deploying ML/AI models such as deep neural networks, fine-tune foundation language models such as LLMs, VLMs, etc.

• Model Training Workflows

  : Familiarity with training-validation pipelines, k-fold cross-validation, early stopping,hyperparameter tuning, etc.

• Evaluation Metrics:

  Experience evaluating models using confusion matrix, PR curves, F1 score, accuracy, ROC-AUC, etc.

• Frameworks:

  Proficient in Python and PyTorch with strong coding practices (clean, modular, testable)

• Tools:

  Experience with model libraries and hubs such as Hugging Face Transformers, TorchVision, etc.

• Data Handling:

  Ability to manage large datasets, custom data loaders, and data augmentation workflows

• Deployment

  : Experience with model packaging (TorchScript, ONNX) and serving (FastAPI, TorchServe)

• Experimentation & Reproducibility

  : Familiarity with tools like Weights & Biases, MLflow, or equivalent

Desirable Skills

• Exposure to Agentic AI or orchestration frameworks like LangChain, LangGraph etc.
• Understanding of vector databases, embedding stores, and RAG pipelines
• Apply inference optimization techniques such as quantization, pruning, and distillation
• Hands-on with knowledge distillation and other model compression techniques
• Contributions to open-source ML projects or academic research

• Cloud AI Platforms: Preference for experience with Amazon SageMaker, Azure AI Services, Google Vertex AI, or Azure AI Foundry

🎓 Education Requirement:

• B.Tech. / M.Tech. / MS in Computer Science or related technical disciplines.

What We Look For

• Strong foundations in Mathematics, algorithmic thinking, and ML system design
• Curiosity-driven mindset and a passion for solving complex problems
• Ability to convert ideas into scalable and efficient solutions
• Desire to learn and grow in a high-performance, innovation-first environment
• Clear communication and collaborative problem-solving skills