Cutting Edge AI Specialist

Machine Learning EngineerAbout the RoleWe are seeking an experienced Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will be responsible for designing, validating, and integrating cutting-edge machine learning models and algorithms. Collaborate closely with cross-functional teams, including data scientists, to recognize and establish project objectives.Core Responsibilities:Machine Learning Development: Develop, validate, and implement machine learning models and algorithms using deep learning frameworks such as PyTorch and TensorFlow.Collaboration: Collaborate with data scientists and other stakeholders to understand and define project goals.Data Infrastructure Maintenance: Maintain data infrastructure and ensure scalability and efficiency of data-related operations.Stay Updated: Stay abreast of the latest developments in the field of AI and recommend ways to implement them in our operations.Communication: Communicate complex data findings clearly and understandably to non-technical stakeholders.Adhere to Guidelines: Adhere to data privacy and security guidelines.Lifecycle Participation: Participate in the entire AI project lifecycle, from concept to deployment and maintenance.Required Skills and QualificationsFundamentals: Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.Experience: Experience with mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, bandwidth, and compute.Vector Databases: Experience with Vector databases like Qdrant, ChromaDB, Pinecone, PGVector or similar.Large Language Models: Experience with Large language Models like GPT 3.5, GPT 4, GPT 4.o, Llama, Gemini, Mistral etc.Agentic AI Workflows: Experience in design, build, and optimization of agentic AI workflows that enable autonomous reasoning, decision-making, and tool interaction using frameworks like LangChain, LangGraph, CrewAI, etc.Generative AI Solutions: Experience in implementation and fine-tuning Generative AI solutions (e.g., LLMs, multimodal models) for various business use cases.LLM Integration Framework: Experience in LLM integration framework like Llamaindex, Ragas, etcML Model Development: Experience with ML Models from definition to deployment, including training, quantization, sparsity, model preprocessing, and deployment.Programming Languages: Proficiency in Python development in a Linux environment and using standard development tools.Deep Learning Frameworks: Experience with deep learning frameworks (such as PyTorch, Tensorflow, Keras, Spark).Artificial Neural Networks: Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs).Computer Vision and Recommendation Systems: Experience in training, tuning, and deploying ML models for Computer Vision (e.g., ResNet), and/or Recommendation Systems (e.g., DLRM).Distributed Systems: Experience deploying ML workloads on distributed systems.Leadership and Communication: Self-motivated team player with a strong sense of ownership and leadership.Research and Documentation: Strong verbal, written, and organizational skills for effective communication and documentation.Publication Record: Research background with a publication record.Cloud Computing and Information Security: Work experience at a cloud provider or AI compute/sub-system company.Cloud Services: Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud.Information Security: Experience with information security and secure development best practices.QualificationsEducation: Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field.Experience: 2-4 yrs of hands-on experience in AI/ML