Machine Learning Engineer

Tasks

• Develop, deploy, and optimize machine learning and AI solutions to tackle complex business challenges.
• Creating multi-agent systems and equipping AI models with functions and the ability to call tools.
• Designing and implementing RAG systems to embed AI responses in enterprise data.
• Evaluate and integrate AI models (e.g., LLMs) to ensure optimal performance and reliability.
• Optimizing agent workflows and AI agents for production use cases.
• Testing and optimizing system prompts and few-shot examples to ensure accurate, consistent, and safe AI outputs.
• Performance evaluation of machine learning and AI models using appropriate metrics, evaluation datasets, and techniques, and continuous iteration and improvement.
• Collaborate with platform teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes.
• Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions.

Requirements

• Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization.
• Ability to effectively manage personal workflows, prioritize tasks, manage schedules, and deliver high-quality results on time.
• A continuous willingness to learn, with a passion for staying up to date on the latest developments in machine learning and artificial intelligence.
• Attention to detail and a commitment to writing high-quality, reliable, and maintainable code.
• Proven experience with large language models (LLMs).
• A solid understanding of AI agents and agent workflows, LLM orchestration frameworks, and thought patterns.
• Experience with data preprocessing, feature engineering, and model selection and evaluation techniques.
• Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization.
• Understanding of software development best practices, including version control, testing, and documentation.
• Excellent problem-solving and debugging skills, with the ability to identify and resolve problems quickly and effectively.

We offer