AI and Machine Learning Engineer

As an AI and Machine Learning engineer at Dailoqa, you will play a crucial role in shaping the future of Financial Services clients and the company. Working directly with the founding team, you will have the opportunity to apply the latest AI techniques to address real challenges faced by Financial Services clients. Your responsibilities will involve designing, building, and refining datasets to evaluate and enhance our solutions, as well as contributing to strategy and product ideation sessions to influence our product and solution roadmap. Key Responsibilities: - **Agentic AI Development**: Build scalable multi-modal Large Language Model (LLM) based AI agents using frameworks like LangGraph, Microsoft Autogen, or Crewai. - **AI Research and Innovation**: Research and develop innovative solutions for relevant AI problems, including Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, fine-tuning, and reasoning in LLMs. - **Technical Expertise**: Demonstrate proficiency in a technology stack comprising Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, and React. - **LLM and NLP Experience**: Utilize hands-on experience with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve practical problems. - **Dataset Development**: Showcase a strong track record in constructing datasets for training and evaluating machine learning models. - **Customer Focus**: Engage deeply in the domain, grasp the problem intricacies, and prioritize delivering value to the customer. - **Adaptability**: Excel in a dynamic environment and exhibit enthusiasm about contributing to an early-stage venture. - **Model Deployment and Management**: Automate model deployment, monitoring, and retraining procedures. - **Collaboration and Optimization**: Collaborate with data scientists to review, refactor, and optimize machine learning code. - **Version Control and Governance**: Implement version control and governance for models and data. Required Qualifications: - Bachelor's degree in computer science, Software Engineering, or a related field - 4-8 years of experience in MLOps, DevOps, or related roles - Strong programming skills and familiarity with Python-based deep learning frameworks like Pytorch, JAX, Tensorflow - Sound understanding and knowledge of machine learning concepts - Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform Desired Skills: - Experience with experiment tracking and model versioning tools - Proficiency in the technology stack: Python, LlamaIndex / LangChain, PyTorch, HuggingFace, FastAPI, Postgres, SQLAlchemy, Alembic, OpenAI, Docker, Azure, Typescript, React. - Knowledge of data pipeline orchestration tools like Apache Airflow or Prefect - Familiarity with software testing and test automation practices - Understanding of ethical considerations in machine learning deployments - Strong problem-solving abilities and adeptness in a fast-paced environment Join us at Dailoqa and be part of a team that values innovation, collaboration, and relentless curiosity. If you are proactive, adaptable, and keen on making a direct impact on success, apply now and embark on a journey of growth and fun in the world of AI and Machine Learning within the financial services industry.,