Senior Machine Learning Engineer - I

Requirements:

• Bachelor's or Master's degree in Science or Engineering with strong programming, data science, critical thinking, and analytical skills.
• 5+ years of experience building in ML and Data science.
• Recent demonstrable hands-on experience with LLMs - integrating off-the-shelf LLMs, fine-tuning smaller models, building RAG pipelines, designing agentic flows, and other optimization techniques with LLMs.
• Strong conceptual understanding of foundational models, transformers, and related research.
• Strong conceptual understanding of the basics of machine learning and deep learning, with expertise in Computer Vision and Natural Language Processing.
• Recent demonstrable experience with managing large datasets for AI projects.
• Experience with implementing AI projects in Python and working knowledge of associated Python libraries - numpy, scipy, pandas, sklearn, matplotlib, nltk, etc.
• Experience with Hugging Face, Spacy, BERT, Tensorflow, Torch, OpenRouter, Modal, and similar services/frameworks.
• Ability to write clean, efficient, and bug-free code.
• Proven ability to lead initiatives from concept to operation while navigating challenges effectively.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills.
• Recent experience with implementing state-of-the-art scalable AI pipelines for extracting data from unstructured / semi-structured sources and converting it into structured information, along with the necessary technical infrastructure to support deployment.
• Experience with cloud platforms (AWS, GCP, Azure), containerization (Kubernetes, ECS, etc. ), and managed services like Bedrock, SageMaker, etc.
• Experience with MLOps practices, e. g., model monitoring, feedback pipelines, CI/CD flows, and governance best practices.
• Experience working with applications hosted on AWS or Django web frameworks.
• Familiarity with databases and web application architecture.
• Experience working with OCR tools or PDF processing libraries.
• Completed academic or online specializations in Machine Learning or Deep Learning.
• Track record of publishing research in top-tier conferences and journals.
• Participation in competitive programming (e. g., Kaggle competitions) or contributions to open-source projects.
• Experience working with geographically distributed teams across multiple time zones.

Skills

LLM, ML, Python, generative AI, large language model, machine learning