New opportunity

AI Engineer 1

Millennium · Bangalore, India

About this role

Millennium’s AI/ML team develops AI solutions and supporting technology for portfolio managers, researchers, risk managers, and other business functions. This AI Engineer role focuses on applying machine learning to research, modeling, risk, and trading-related use cases in the firm’s Information Technology organization.

Responsibilities

  • Work with business stakeholders, quantitative teams, and market researchers to understand complex problems and identify high-impact AI/ML opportunities.
  • Experiment with and iterate on AI/ML solutions, then bring them into production.
  • Build data and AI/ML infrastructure, tools, and frameworks for data preparation, deployment, model measurement, and retraining. The team’s infrastructure work also includes data wrangling and feature stores.

Qualifications

  • Strong knowledge of current AI and machine learning techniques, including large language models, deep learning, and reinforcement learning; experience using LLMs, prompt engineering, parameter-efficient fine-tuning, and fine-tuning.
  • Strong computer science fundamentals and software engineering skills; proficiency in Python and at least one additional language, such as Java, C++, or C#.
  • Experience with a cloud platform such as AWS, Azure, or Google Cloud, and the ability to build and evaluate AI models and tools using quantifiable metrics.
  • Strong problem-solving and communication skills, with the ability to work independently and collaborate with technical and business stakeholders.

Preferred

Experience in a fast-paced, startup-like environment; an advanced degree in Computer Science, AI, Machine Learning, or a related field; financial-services AI experience; and 3+ years of relevant experience. The position is listed as full-time in Bangalore, Karnataka, India.

Skills for this role

Machine LearningLarge Language ModelsDeep LearningReinforcement LearningPythonJavaC++C#AWSAzureGoogle CloudPrompt EngineeringParameter-Efficient Fine-TuningModel Fine-TuningModel EvaluationData PreparationFeature StoresModel DeploymentModel RetrainingSoftware EngineeringProblem-SolvingCommunication

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