While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role : Machine Learning Engineer
Experience : 1-3 Years
Location: Bangalore
Notice Period : 0-15 Days
Key Responsibilities
• Implement and deploy generative AI models (e.g., large language models, diffusion models) based on architectural guidance and research specifications.
• Build and optimize agentic AI systems - autonomous agents that perceive, reason, and act effectively in complex environments using frameworks like LangChain, CrewAI, and Google Agent Development Kit (ADK).
• Work with Model Context Protocol (MCP) to enable seamless integration between AI agents and external tools and data sources.
• Develop production-ready implementations by translating insights from recent ML/AI research papers into functional code.
• Apply core NLP concepts including tokenization, embeddings, attention mechanisms, and transformer architectures in practical applications.
• Collaborate with senior engineers and data scientists to build scalable ML pipelines and deploy models into production environments.
• Develop and integrate APIs using FastAPI for model serving and application development.
• Implement prompt engineering techniques to optimize model performance and output quality.
• Conduct model evaluation and experimentation to assess performance, accuracy, and efficiency of ML systems.
• Maintain comprehensive technical documentation for implementations, experiments, and deployment processes.
• Learn from existing codebases and contribute to improving ML engineering best practices within the team.
• Take ownership of assigned tasks and ensure timely delivery of high-quality implementations.
• Support research efforts by implementing proof-of-concepts and contributing to internal knowledge sharing.
• Stay updated with the latest developments in generative AI, agents, and ML technologies through continuous learning.
Qualifications
• Bachelor's degree in Computer Science, Machine Learning, AI, or related fields with 1.5 to 3 years of industry experience in Machine Learning engineering or related roles.
• Strong programming skills in Python with hands-on experience in implementing ML solutions.
• Proficiency with deep learning frameworks such as PyTorch, TensorFlow, or similar.
• Experience working with Large Language Models (LLMs) and generative AI technologies.
• Understanding of Natural Language Processing (NLP) fundamentals and transformer architectures.
• Familiarity with Hugging Face Transformers library for model implementation and fine-tuning.
• Experience with ML libraries including Scikit-learn, Pandas, and NumPy for data processing and model development.
• Hands-on experience with LLM APIs such as OpenAI API and Anthropic API.
• Knowledge of agent development frameworks like LangChain or CrewAI.
• Experience with version control systems (Git, GitLab) and collaborative development workflows.
• Demonstrated ability to read research papers and translate them into working implementations.
• Strong problem-solving skills with attention to detail and code quality.
• Excellent communication and collaboration skills for working in cross-functional teams.
Preferred Skills
• Experience with advanced deep learning techniques including fine-tuning, transfer learning, and model optimization.
• Knowledge of reinforcement learning, diffusion models, or multimodal learning architectures.
• Knowledge of transformer architecture variants (BERT, GPT, T5) and their practical applications.
• Familiarity with model evaluation methodologies, experimentation frameworks, and A/B testing for ML models.
• Experience with prompt engineering techniques and systematic prompt optimization strategies.
• Hands-on experience building and deploying generative AI applications using Large Language Models.
• Exposure to Model Context Protocol (MCP) or similar agent-tool integration frameworks.
• Experience with Google Agent Development Kit (ADK) or similar agentic frameworks.
• Proficiency with agent orchestration frameworks like LangChain or CrewAI for building complex AI workflows.
• Knowledge of MLOps practices including model versioning, logging and tracing, and monitoring in production.
• Familiarity with Google Cloud Platform (GCP) services including Vertex AI, Cloud Functions, BigQuery, and Cloud Storage.
• Experience with API development and microservices architecture using FastAPI.
• Experience with containerization using Docker and understanding of deployment workflows.
• Knowledge of container orchestration tools like Kubernetes.
• Familiarity with other cloud platforms (AWS, Azure) and their ML services.
• Strong technical documentation skills for code, experiments, and system architectures.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Top Skills
What We Do
Quantiphi is an award-winning AI-first digital engineering company driven by the desire to solve transformational problems at the heart of business.
Quantiphi solves the toughest and complex business problems by combining deep industry experience, disciplined cloud, and data-engineering practices, and cutting-edge artificial intelligence research to achieve quantifiable business impact at unprecedented speed.
