Job Title: AI/LLM Architect | Machine Learning Architect

Location: ( Remote )

Job Type: Full-time

Salary: $180,000 - $250,000 per year

Job Description

We’re seeking an experienced AI/LLM Architect to lead the design and implementation of our large language model and machine learning infrastructure. In this senior technical role, you’ll architect scalable AI systems, guide our ML strategy, and work closely with engineering, product, and data science teams to deploy cutting-edge LLM solutions that drive business value. This is a high-impact position for someone passionate about pushing the boundaries of what’s possible with AI.

Key Responsibilities

• Design and architect end-to-end LLM and ML systems at scale, including model selection, fine-tuning strategies, and deployment pipelines

• Lead the development of AI/ML infrastructure that supports training, evaluation, and production deployment of large language models

• Define best practices for prompt engineering, RAG (Retrieval-Augmented Generation) implementations, and LLM orchestration

• Evaluate and select appropriate foundation models (GPT, Claude, Llama, Mistral, etc.) based on use case requirements

• Architect solutions for model fine-tuning, including LoRA, QLoRA, and full fine-tuning approaches

• Design and implement robust evaluation frameworks to measure model performance, accuracy, and safety

• Collaborate with data engineering teams to build scalable data pipelines for model training and inference

• Establish MLOps practices including model versioning, monitoring, A/B testing, and continuous improvement

• Provide technical leadership and mentorship to ML engineers and data scientists

• Stay current with the rapidly evolving LLM landscape and emerging AI technologies

• Ensure AI systems are built with security, privacy, and ethical considerations in mind

• Partner with stakeholders to translate business requirements into technical AI/ML solutions

• Optimize model performance, latency, and cost-efficiency for production environments

Required Skills and Qualifications

• 7+ years of experience in machine learning, with at least 3 years focused on LLMs or NLP

• Deep expertise in working with large language models (OpenAI, Anthropic, open-source models)

• Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers)

• Proven experience architecting and deploying ML systems at scale in production environments

• Expertise in LLM techniques including prompt engineering, few-shot learning, fine-tuning, and RLHF

• Experience with vector databases and embedding models for RAG implementations (Pinecone, Weaviate, ChromaDB, etc.)

• Strong understanding of transformer architectures and attention mechanisms

• Experience with model optimization techniques (quantization, pruning, distillation)

• Proficiency with cloud platforms (AWS, GCP, Azure) and their ML services (SageMaker, Vertex AI, Azure ML)

• Knowledge of MLOps tools and practices (MLflow, Kubeflow, Weights & Biases, etc.)

• Experience with containerization (Docker, Kubernetes) for ML workloads

• Strong understanding of distributed training and inference strategies

• Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders

• Master’s or PhD in Computer Science, Machine Learning, or related field (or equivalent experience)

Preferred Qualifications

• Experience with LLM fine-tuning at scale using techniques like LoRA, QLoRA, or full parameter fine-tuning

• Hands-on experience with LLM frameworks like LangChain, LlamaIndex, or Semantic Kernel

• Knowledge of advanced techniques like Constitutional AI, chain-of-thought prompting, or agent-based systems

• Experience building multimodal AI systems (vision-language models, audio processing)

• Background in deploying models on edge devices or optimizing for low-latency inference

• Contributions to open-source ML/AI projects or published research in top-tier conferences

• Experience with AI safety, alignment, and responsible AI practices

• Knowledge of GPU optimization and parallel computing frameworks (CUDA, Ray, DeepSpeed)

• Experience with data labeling platforms and synthetic data generation

• Familiarity with reinforcement learning from human feedback (RLHF) pipelines

Technical Stack(s)

• LLM Platforms: OpenAI API, Anthropic Claude, Hugging Face, Azure OpenAI

• ML Frameworks: PyTorch, TensorFlow, JAX, Hugging Face Transformers

• Vector DBs: Pinecone, Weaviate, Qdrant, Milvus, ChromaDB

• Orchestration: LangChain, LlamaIndex, Haystack

• MLOps: MLflow, Weights & Biases, Neptune.ai, Kubeflow

• Infrastructure: AWS/GCP/Azure, Kubernetes, Docker, Terraform

• Monitoring: Prometheus, Grafana, DataDog

What We Offer

• Competitive salary ($180,000 - $250,000 based on experience)

• Significant equity/stock options package

• Comprehensive health, dental, and vision insurance

• 401(k) with generous company match

• Unlimited PTO policy

• $5,000+ annual professional development budget for conferences, courses, and certifications

• Access to cutting-edge AI tools and compute resources

• Remote-first culture with flexible work arrangements

• Opportunity to work on challenging problems with real-world impact

• Collaborative environment with top-tier AI/ML talent

• Conference speaking opportunities and support for publishing research

Email resume to careers@oliego.com