Indotronix UK
ML Engineers
Indotronix UK, Mountain View, California, us, 94039
Location:
Mountain View, CA, California, United States Posted:
03/11/2023 Hello Professionals, We have an urgent requirement for
ML Engineers . Please have a look at the below job description. If interested, please share your updated resume by emailing me at
pavan@zortechsolutions.ca
or share any references. Duration:
6+ Months Job Description: Must have skills: Basic experience with generative AI, LLM operations, AI assistant, prompt engineering, embeddings, AI background, machine learning. Responsibilities: Develop, Train, Finetune, and Deploy large language models for text completion and chats in different applications including coding, NLU, NLG, IRQA, machine translation, and dialog, reasoning, and tool systems. Apply instruction tuning, reinforcement learning from human feedback (RLHF), and parameter efficient finetuning such as p-tuning, adaptors, LoRA, and so on to improve LLMs for different use cases. Measure and benchmark model and application performance. Analyze model accuracy and bias and recommend the next course of action & improvements. Drive the gathering, building, and annotation of domain-specific datasets to train LLMs for different tasks and applications. Gather know-how on datasets for LLM training & evaluation. Characterize performance and quality metrics across platforms for various AI and system components. Qualifications: Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math with 3+ years of experience. Excellent programming skills in Python with strong fundamentals in programming, optimizations, and software design. Strong knowledge of ML/DL techniques, algorithms, and tools with exposure to CNN, RNN (LSTM), Transformers (BERT, BART, GPT/T5, Megatron, LLMs). Hands-on experience with conversational AI technologies like Natural Language Understanding, Natural Language Generation, dialog systems (including system integration, state tracking, and action prediction), Information retrieval, and Question and Answering, Machine Translation, etc. Experience with training BERT, GPT for different NLP and dialog system tasks using “PyTorch” Deep Learning Frameworks and performing NLP data wrangling and tokenization. Understanding of MLOps lifecycle and experience with MLOps workflows & traceability and versioning of datasets including know-how of database management and queries (in SQL, MongoDB, etc). Knowledge of end-to-end MLOps platforms such as Kubeflow, MLFlow, AirFlow.
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Mountain View, CA, California, United States Posted:
03/11/2023 Hello Professionals, We have an urgent requirement for
ML Engineers . Please have a look at the below job description. If interested, please share your updated resume by emailing me at
pavan@zortechsolutions.ca
or share any references. Duration:
6+ Months Job Description: Must have skills: Basic experience with generative AI, LLM operations, AI assistant, prompt engineering, embeddings, AI background, machine learning. Responsibilities: Develop, Train, Finetune, and Deploy large language models for text completion and chats in different applications including coding, NLU, NLG, IRQA, machine translation, and dialog, reasoning, and tool systems. Apply instruction tuning, reinforcement learning from human feedback (RLHF), and parameter efficient finetuning such as p-tuning, adaptors, LoRA, and so on to improve LLMs for different use cases. Measure and benchmark model and application performance. Analyze model accuracy and bias and recommend the next course of action & improvements. Drive the gathering, building, and annotation of domain-specific datasets to train LLMs for different tasks and applications. Gather know-how on datasets for LLM training & evaluation. Characterize performance and quality metrics across platforms for various AI and system components. Qualifications: Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math with 3+ years of experience. Excellent programming skills in Python with strong fundamentals in programming, optimizations, and software design. Strong knowledge of ML/DL techniques, algorithms, and tools with exposure to CNN, RNN (LSTM), Transformers (BERT, BART, GPT/T5, Megatron, LLMs). Hands-on experience with conversational AI technologies like Natural Language Understanding, Natural Language Generation, dialog systems (including system integration, state tracking, and action prediction), Information retrieval, and Question and Answering, Machine Translation, etc. Experience with training BERT, GPT for different NLP and dialog system tasks using “PyTorch” Deep Learning Frameworks and performing NLP data wrangling and tokenization. Understanding of MLOps lifecycle and experience with MLOps workflows & traceability and versioning of datasets including know-how of database management and queries (in SQL, MongoDB, etc). Knowledge of end-to-end MLOps platforms such as Kubeflow, MLFlow, AirFlow.
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