Intuitive.Cloud ยท 4 hours ago
LLM Engineer
United States
Contract
Remote
Senior Level
7+ years exp
Maximize your interview chancesInformation Technology & Services
Hiring Manager
Mitesh Kumar
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Responsibilities
Fine-tune pre-trained large language models (e.g., GPT, LLaMA, Falcon) for specific use cases and domain-specific tasks.
Design and implement custom data preprocessing and augmentation pipelines to improve model performance.
Deploy and optimize LLMs on on-premise environments, ensuring resource efficiency.
Configure and manage GPU clusters for high-performance local inference and training.
Develop robust CI/CD pipelines to automate model versioning, testing, and deployment.
Implement Continuous Learning (CL) pipelines to retrain models with fresh data and monitor performance.
Establish comprehensive monitoring systems for tracking model performance, drift, and latency.
Optimize inference workflows for low-latency and high-throughput performance.
Collaborate with cross-functional teams, including data scientists, DevOps engineers, and software developers, to integrate LLMs into production systems.
Maintain detailed documentation of workflows, pipelines, and model changes.
Stay updated with the latest advancements in LLMs, fine-tuning techniques, and LLMOps tools.
Experiment with new architectures and methodologies to improve efficiency and scalability.
Qualification
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Required
7+ years of programming experience in machine learning or AI-related roles.
At least 3 years of hands-on experience fine-tuning and deploying large language models.
Proficiency in fine-tuning frameworks like Hugging Face Transformers, LoRA (Low-Rank Adaptation), or PEFT (Parameter Efficient Fine-Tuning).
Experience with pre-trained models such as GPT, BERT, T5, LLaMA, or Falcon.
Knowledge of prompt engineering and evaluation techniques.
Strong experience in deploying LLMs locally on GPUs and optimizing for performance.
Familiarity with tools like NVIDIA Triton Inference Server, TensorRT, and DeepSpeed.
Proficiency in tools like MLflow, DVC, or Kubeflow for model lifecycle management.
Expertise in CI/CD tools (e.g., GitLab Actions, Jenkins) and integrating them with machine learning pipelines.
Experience implementing Continuous Learning pipelines for model retraining.
Strong Python programming skills with experience in libraries such as PyTorch and TensorFlow.
Proficiency in scripting and automation (e.g., Bash, Terraform).
Experience with Kubernetes, Docker, and managing GPU clusters.
Familiarity with hybrid cloud and on-premise deployments.
Excellent problem-solving skills and attention to detail.
Strong collaboration and communication abilities.
Self-motivated with a proactive approach to learning and experimentation.
Preferred
Familiarity with distributed training frameworks (e.g., Horovod, PyTorch DDP).
Experience working with knowledge bases, RAG (Retrieval-Augmented Generation), or hybrid AI systems.
Strong understanding of secure deployment practices for sensitive applications.
Company
Intuitive.Cloud
Intuitive.Cloud is one of the fastest-growing (INC 5000, CRN) Cloud & SDx solutions and services providers supporting enterprise customers on a global scale.
501-1000 employees
H1B Sponsorship
Intuitive.Cloud has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2023 (4)
2022 (1)
2021 (3)
2020 (4)
Funding
Current Stage
Late StageLeadership Team
Jay Modh
Founder and CEO
Company data provided by crunchbase
