AIML Engineer

Job Overview:
We are seeking a talented and experienced AI/ML Engineer to design develop and deploy cutting-edge artificial intelligence and machine learning solutions. This role focuses on the core ML lifecycle from data handling and model development to deployment optimization and monitoring in production environments. The ideal candidate will be passionate about leveraging the latest advancements in AI particularly in areas like Large Language Models (LLMs) and Natural Language Processing (NLP) to build intelligent systems that drive innovation and solve complex problems.
Key Responsibilities:

• Design build train and fine-tune various machine learning models with a strong focus on Large Language Models (LLMs) and Natural Language Processing (NLP) models.
• Collaborate with data scientists and engineers to acquire preprocess and manage data required for model training and evaluation.
• Implement and utilize AI/ML frameworks and libraries (e.g. PyTorch TensorFlow scikit-learn Hugging Face transformers).
• Develop and implement APIs and integration points to make AI/ML models and services accessible to other engineering teams and systems.
• Deploy manage and monitor models and AI services in production environments ensuring performance scalability and reliability.
• Utilize specialized AI development tools and frameworks such as LangChain AutoGen or other intelligent agent frameworks.
• Implement MLOps practices for model versioning continuous integration/continuous deployment (CI/CD) monitoring and retraining.
• Optimize models and inference pipelines for performance efficiency and cost-effectiveness.
• Stay updated with the latest research techniques and tools in the AI/ML field and propose new approaches.
• Collaborate effectively with product managers data scientists and other engineering teams (e.g. backend frontend) to translate requirements into technical designs and integrate AI capabilities into products.

Required Skills and Experience:

• 4 years of experience in a technical role with a strong focus on Machine Learning and AI development (ideally 2 years dedicated AI/ML experience).
• Proficiency in Python and standard ML/AI libraries (e.g. NumPy Pandas scikit-learn TensorFlow PyTorch).
• Solid understanding of core Machine Learning concepts algorithms model evaluation techniques and deployment strategies.
• Hands-on experience building training and deploying models especially LLMs and NLP models.
• Experience working with LLM APIs (e.g. OpenAI Anthropic) and relevant libraries/frameworks (e.g. Hugging Face transformers LangChain AutoGen).
• Familiarity with vector databases/stores (e.g. Pinecone Weaviate FAISS) and techniques like RAG (Retrieval Augmented Generation).
• Experience with model deployment tools and MLOps practices.
• Familiarity with cloud platforms (AWS GCP Azure) and containerization technologies (Docker Kubernetes) for model deployment.
• Understanding of API design principles for serving machine learning models.
• Strong problem-solving skills and ability to translate business problems into technical AI/ML solutions.
• Excellent communication and collaboration skills.

Nice-to-Haves:

• Experience with specific cloud ML services (e.g. AWS SageMaker Google AI Platform/Vertex AI Azure ML).
• Knowledge of data engineering pipelines and ETL processes.
• Experience with distributed training frameworks.
• Contributions to open-source AI/ML projects.
• Advanced degree (Masters or PhD) in Computer Science Machine Learning Data Science or a related quantitative field.