Job Description

About the Role

We are seeking a talented LLM (Large Language Model) Engineer to join our growing AI/ML team. The ideal candidate will have hands-on experience working with modern natural language processing (NLP) systems, large-scale model training, fine-tuning, and deployment. You will collaborate closely with data scientists, ML engineers, and product teams to design and optimize solutions powered by cutting-edge language models.

Key Responsibilities

Design, train, fine-tune, and evaluate large language models (LLMs) for various use cases. Implement prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques to optimize model outputs. Build pipelines for data preprocessing, tokenization, and dataset curation. Optimize model performance (latency, throughput, and cost-efficiency) for production-scale deployment. Integrate LLMs into applications, APIs, and business workflows. Research and experiment with new architectures, frameworks, and techniques in NLP and generative AI. Collaborate with cross-functional teams to translate product requirements into scalable AI solutions. Ensure ethical AI practices, data security, and compliance with AI governance standards.

Required Qualifications

Minimum 2 years of professional experience in AI/ML engineering or NLP. Strong programming skills in Python and familiarity with libraries such as PyTorch, TensorFlow, Hugging Face Transformers. Experience with fine-tuning LLMs (e.g., GPT, LLaMA, Falcon, Mistral, etc.). Knowledge of prompt engineering, embeddings, and vector databases (e.g., FAISS, Pinecone, Weaviate). Proficiency in cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes). Understanding of distributed systems, model optimization, and deployment strategies.

Preferred Qualifications

Experience with RAG (Retrieval-Augmented Generation) and knowledge of LangChain / LlamaIndex. Familiarity with MLOps tools (MLflow, Weights & Biases, Vertex AI, SageMaker). Background in data engineering and pipeline automation. Publications, open-source contributions, or projects in NLP/LLMs. Strong problem-solving and research mindset.

Perks and benefits of working at Algoscale:

Opportunity to collaborate with leading companies across the globe. Opportunity to work with the latest and trending technologies. Competitive salary and performance-based bonuses. Co?mprehensive group health insurance. Flexible working hours and remote work options. (For some positions only) Generous vacation and paid time off. * Professional learning and development programs and certifications.