ShyftLabs
Data Scientist – Large Language Model (LLM)
Job Description
Position Overview:ShyftLabs is searching for a talented Data Scientist with expertise in Large Language Model (LLM) solutions to join our dynamic team. As a key member of our research and development team, you will be responsible for designing, implementing, and optimizing state-of-the-art LLM solutions to address complex business challenges. The ideal candidate will have a strong background in machine learning, natural language processing, and software development, along with a proven track record of delivering high-quality AI solutions.
ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.
Job Description:Conduct cutting-edge research in the field of Large Language Models, including exploring novel architectures, algorithms, and techniques to improve model performance, efficiency, and scalability.Design, develop, and implement advanced LLM solutions tailored to specific business use cases, leveraging techniques such as transfer learning, fine-tuning, and model distillation.Collaborate with data engineers and domain experts to preprocess and curate large-scale datasets for training and evaluation of LLMs. Perform feature engineering and data augmentation to enhance model robustness and generalization.Train and fine-tune LLMs on diverse datasets using state-of-the-art techniques and frameworks (e.g., TensorFlow, PyTorch). Develop robust evaluation metrics and methodologies to assess model performance, accuracy, and effectiveness.Deployment and Optimization: Deploy LLM solutions into production environments, ensuring scalability, reliability, and performance. Optimize models for inference speed, memory footprint, and energy efficiency, taking into account hardware constraints and resource limitations.Work closely with cross-functional teams, including software engineers, product managers, and business stakeholders, to understand requirements, define project goals, and deliver actionable insights and solutions. Communicate findings and results effectively through presentations, reports, and documentation.Stay abreast of the latest advancements in LLM research, machine learning algorithms, and AI technologies. Continuously experiment with new methodologies, tools, and frameworks to enhance the capabilities of LLM solutions and drive innovation within the organization.
Basic Qualifications:Master’s or Ph.D. degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field.Minimum 4+ years of hands-on experience in Python development, with a particular focus on data science, machine learning, and AI. Strong theoretical and practical knowledge of machine learning, deep learning, and natural language processing.Hands-on experience with developing and fine-tuning Large Language Models (e.g., GPT, BERT, XLNet) using deep learning frameworks such as TensorFlow or PyTorch.Proficiency in programming languages such as Python, along with experience in software development and version control tools (e.g., Git).Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and distributed computing frameworks (e.g., Apache Spark) is a plus.Excellent problem-solving skills, analytical thinking, and attention to detail.Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, multidisciplinary team environment.Publications or contributions to relevant conferences, journals, or open-source projects would be advantageous.
We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is preferably hybrid, with 2 days per week spent in our downtown Toronto office. We pride ourselves on the growth of our employees, offering extensive learning and development resources.
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.
ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.
Job Description:Conduct cutting-edge research in the field of Large Language Models, including exploring novel architectures, algorithms, and techniques to improve model performance, efficiency, and scalability.Design, develop, and implement advanced LLM solutions tailored to specific business use cases, leveraging techniques such as transfer learning, fine-tuning, and model distillation.Collaborate with data engineers and domain experts to preprocess and curate large-scale datasets for training and evaluation of LLMs. Perform feature engineering and data augmentation to enhance model robustness and generalization.Train and fine-tune LLMs on diverse datasets using state-of-the-art techniques and frameworks (e.g., TensorFlow, PyTorch). Develop robust evaluation metrics and methodologies to assess model performance, accuracy, and effectiveness.Deployment and Optimization: Deploy LLM solutions into production environments, ensuring scalability, reliability, and performance. Optimize models for inference speed, memory footprint, and energy efficiency, taking into account hardware constraints and resource limitations.Work closely with cross-functional teams, including software engineers, product managers, and business stakeholders, to understand requirements, define project goals, and deliver actionable insights and solutions. Communicate findings and results effectively through presentations, reports, and documentation.Stay abreast of the latest advancements in LLM research, machine learning algorithms, and AI technologies. Continuously experiment with new methodologies, tools, and frameworks to enhance the capabilities of LLM solutions and drive innovation within the organization.
Basic Qualifications:Master’s or Ph.D. degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field.Minimum 4+ years of hands-on experience in Python development, with a particular focus on data science, machine learning, and AI. Strong theoretical and practical knowledge of machine learning, deep learning, and natural language processing.Hands-on experience with developing and fine-tuning Large Language Models (e.g., GPT, BERT, XLNet) using deep learning frameworks such as TensorFlow or PyTorch.Proficiency in programming languages such as Python, along with experience in software development and version control tools (e.g., Git).Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and distributed computing frameworks (e.g., Apache Spark) is a plus.Excellent problem-solving skills, analytical thinking, and attention to detail.Strong communication and collaboration skills, with the ability to work effectively in a fast-paced, multidisciplinary team environment.Publications or contributions to relevant conferences, journals, or open-source projects would be advantageous.
We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. The role is preferably hybrid, with 2 days per week spent in our downtown Toronto office. We pride ourselves on the growth of our employees, offering extensive learning and development resources.
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse and inclusive environment. We encourage qualified applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, nationality, and education levels to apply. If you are contacted for an interview and require accommodation during the interviewing process, please let us know.
