MLOps Engineer

hirify.global delivers hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence.

Overview

As an MLOps Engineer, you will deploy cutting-edge ML/LLMs models to Fortune Global 500 clients and collaborate with Product and DevOps teams and Generative AI researchers to optimize model performance and resource utilization.

What you will do

• Design, develop, and implement ML/LLM pipelines, encompassing data acquisition, preprocessing, model training and tuning, deployment, and monitoring.
• Employ automation tools (GitOps, CI/CD, Docker, Kubernetes) to enhance ML/LLM processes throughout the lifecycle.
• Establish and maintain monitoring and alerting systems to track Large Language Model performance and detect data drift.
• Conduct truth analysis to evaluate the accuracy and effectiveness of Large Language Model outputs.
• Manage and maintain cloud infrastructure (AWS, Azure) for Large Language Model workloads, ensuring cost-efficiency and scalability.
• Stay updated with the latest developments in ML/LLM Ops, integrating these advancements into generative AI platforms and processes.

Requirements

• Bachelor's or master's degree in computer science, Engineering, or a related field.
• Mid - 2+ years or Senior - 5+ years of experience as an ML/LLM engineer in public cloud platforms.
• Proven experience in MLOps, LLMOps, or related roles, with hands-on experience in managing machine/deep learning and large language model pipelines.
• Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering.
• Expertise in model parallelism in model training and serving, and data parallelism/hyperparameter tuning.
• Proficiency in programming languages such as Python, distributed computing tools such as Ray, model parallelism frameworks such as DeepSpeed, Fully Sharded Data Parallel (FSDP), or Megatron LM.
• Relocation package (if applicable).

Nice to have

• Experience in training “Mixture-of-Experts".
• Experience working with different public cloud providers and hybrid environments.
• Experience in real-time streaming applications.
• Experience with Azure Data Lake, Azure Data Factory, Azure RBAC, Application insights - Azure Monitor.

Culture & Benefits

• Indefinite contract.
• Equal pay guaranteed.
• Variable performance bonus.
• Signing bonus.
• We offer work visa sponsorship (If applicable).
• Private health insurance and eligibility for educational budget.