Ai/ml engineer
7 days ago
Core Responsibilities
Develop, validate, and implement machine learning models and algorithms.
Collaborate with data scientists and other stakeholders to understand and define project goals.
Maintain data infrastructure and ensure scalability and efficiency of data-related operations.
Stay abreast of the latest developments in the field of AI/Client and recommend ways to implement them in our operations.
Communicate complex data findings in a clear and understandable manner to non-technical stakeholders.
Adhere to data privacy and security guidelines.
Participate in the entire AI project lifecycle, from concept to deployment and maintenance.
Required Skills
Strong grasp of computer architecture, data structures, system software, and machine learning fundamentals.
Solid theoretical understanding of machine learning.
Experience with mapping NLP models (BERT and GPT) to accelerators and awareness of trade-offs across memory, bandwidth, and compute.
Experience with Vector databases like Chroma Db, Pinecone, PGVector or similar
Experience with Large language Models like GPT 3.5, GPT 4, GPT 4.o, Llama, Gemini, Mistral etc.
Experience in LLM integration framework like langchain, Llamaindex, Agent GPT etc
Experience with ML Models from definition to deployment, including training, quantization, sparsity, model preprocessing, and deployment.
Proficiency in Python development in a Linux environment and using standard development tools.
Experience with deep learning frameworks (such as Py Torch, Tensorflow, Keras, Spark).
Working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Generative Adversarial Networks (GANs).
Experience in training, tuning, and deploying ML models for Computer Vision (e.g., Res Net), and/or Recommendation Systems (e.g., DLRM).
Experience deploying ML workloads on distributed systems.
Self-motivated team player with a strong sense of ownership and leadership.
Strong verbal, written, and organizational skills for effective communication and documentation.
Research background with a publication record.
Work experience at a cloud provider or AI compute/sub-system company.
Knowledge of cloud computing platforms and services, such as AWS, Azure, or Google Cloud.
Qualifications
Bachelor's or higher degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field.
2-4 yrs of hands-on experience in AI/ML
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