Senior Machine Learning Engineer - LLM Models

Job Summary

Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems.

Key Responsibilities
 Create & maintain machine learning pipelines and workflow orchestration. Take development projects to production and implement CI/CD pipelines.
 Continuously monitor the performance of machine learning implementations and identify opportunities for improvement.
 Establish and maintain data pipelines. Ensure operational scalability.
 Develop and deploy scalable tools and services for our clients to handle machine learning training and inference.
 Apply software engineering rigor and best practices to machine learning pipelines.
 Identify and evaluate new technologies to. improve performance, maintainability, and reliability of machine learning solutions.
 Work across teams to bring continuous improvement to engineering processes and tools.
 Facilitate the development and deployment of proof-of-concept machine learning systems.
 Lead the development and fine-tuning of large language models to achieve optimal performance across a range of tasks and domains.

Key Qualifications :
 Degree in computer science, software engineering, mathematics, or a related field.
 At least 3 years of experience in software engineering, and a strong understanding of model deployment and monitoring.
 Experience building data pipelines, deploying machine learning models in production, and monitoring and maintaining their performance.
 Experience embedding monitoring solutions in ML applications.
 Good to have the knowledge of LLM.
 Strong programming skills in python. Experience with automation for deploying machine learning solutions using python/bash scripting.
 Extensive experience with Git, Docker, Kubernetes, and other DevOps tools and a good understanding of Linux for managing servers.
 Experience with cloud-based ecosystems, especially AWS ML services.
 Experience with AWS SageMaker highly preferred.
 Good to have experience in developing, fine-tuning, and optimizing large language models, such as GPT-3, BERT, or similar.
 Exposure to machine learning frameworks and tools.
 Excellent communication and collaboration skills.
 Ability to work independently and in a team-oriented environment.
 Methodical and meticulous towards work and planning.

(ref:hirist.tech,