Sr.AI ML Engineers

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 as a whole. Working directly with the founding team, you will have the opportunity to apply the latest AI techniques to address real-world problems encountered by Financial Services clients. Your responsibilities will include designing, constructing, and enhancing datasets to assess and continually enhance our solutions, as well as engaging in 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 such as LangGraph, Microsoft Autogen, or Crewai. - AI Research and Innovation: Research and develop innovative solutions for relevant AI challenges such as Retrieval-Augmented Generation (RAG), semantic search, knowledge representation, tool usage, 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: Hands-on experience with LLMs, RAG architectures, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems. - Dataset Development: Establish a strong track record of constructing datasets for training and/or evaluating machine learning models. - Customer Focus: Dive deep into the domain, comprehend the problem, and concentrate on delivering value to the customer. - Adaptability: Thrive in a fast-paced environment and demonstrate enthusiasm for joining an early-stage venture. - Model Deployment and Management: Automate model deployment, monitoring, and retraining processes. - 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 similar roles. - Strong programming experience and familiarity with Python-based deep learning frameworks like PyTorch, JAX, Tensorflow. - 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 with 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 skills and ability to work in a fast-paced environment.,