Lead AI Developer and DevOps

5 - 9 years

0 Lacs

Posted:2 days ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Role Overview: As a Machine Learning Engineer at Merkle, your primary responsibility will be to lead the collaboration with ML Engineers and DevOps Engineers to formulate AI designs that can be built, tested, and deployed through the Route to Live and into Production using continuous integration/deployment. Key Responsibilities: - Model fine-tuning: Utilize open-source libraries like DeepSpeed, Hugging Face Transformers, JAX, PyTorch, and TensorFlow to enhance model performance - Model deployment and maintenance: Deploy and manage Large Language Models (LLMs) on cloud platforms - Data curation and preparation: Curate and prepare training data, monitor data quality, and transform, aggregate, and de-duplicate data iteratively - Monitoring and evaluation: Track LLM performance, identify errors, optimize models, and establish monitoring metrics - Infrastructure and DevOps: Implement continuous integration/delivery (CI/CD) pipelines, manage infrastructure for distributed model training, and deploy ML models using containerization technologies like Docker Qualifications Required: - Proficiency in programming languages such as Python and frameworks like PyTorch and TensorFlow - Experience with cloud platforms like AWS, Azure, or GCP, and services like EC2, S3, and SageMaker for scalable model deployment - Familiarity with containerization technologies like Docker and Kubernetes - Knowledge of LLM-specific technologies including vector databases, prompt engineering, and model customization techniques - Understanding of techniques like few-shot and chain-of-thought (CoT) prompting for enhancing model accuracy and response quality Additional Details: Omit this section as there are no additional details of the company mentioned in the job description.,

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