AI/ML Engineer

Job Summary:

As an AI/ML Engineer, you will be a key member of our newly established AI Center of Excellence, driving the development of cutting-edge AI/ML solutions across the organization. You will design, develop, and implement machine learning models and algorithms to address complex enterprise challenges. Collaborating closely with data scientists, software engineers, and various stakeholders, you will ensure the seamless integration of AI capabilities across a diverse range of business applications.

This central team provides a unique opportunity to work with multiple enterprise customers, solving diverse and challenging problems to foster impactful AI adoption across the company.

Key Responsibilities:

• Design, Develop, and Deploy ML Models: Create scalable, production-ready machine learning models using platforms such as Databricks, Azure ML, or Palantir for diverse enterprise applications.
• LLM Integration: Develop AI/ML applications, integrating Large Language Models (LLMs) into Databricks or Palantir, and optimizing their use for specific customer needs.
• RAG Chat Bots Evaluation: Leverage LLMs-as-a-Judge (e.g., llama2-70B judges llama2-7B, or GPT4 judges llama2-70B) to assess and evaluate generative model predictions.
• Collaboration: Work closely with cross-functional teams to understand business requirements and deliver AI-driven solutions tailored to enterprise needs.
• Model Optimization: Optimize machine learning models for performance, accuracy, and scalability, employing techniques such as LLM Pretraining, fine-tuning, RLHF, distillation, LoRA, and quantization.
• Inference Optimization: Build and optimize inference engines/servers, including speculative decoding and co-optimizations for both training and inference.
• Data Preprocessing & Feature Engineering: Implement advanced data preprocessing techniques, feature engineering, and model evaluation methods to maximize model performance.
• Observability & Debugging: Monitor, debug, and troubleshoot AI systems for scalability and performance issues, ensuring optimal functionality and reliability.
• Stay Current with AI/ML Research: Keep up to date with the latest advancements in AI/ML technologies, particularly in LLMs and their applications.
• Documentation: Create top-tier technical documentation, including internal design docs, customer-facing engineering documentation, and data-driven case studies for marketing.
• AI Center of Excellence Contribution: Actively contribute to the growth and success of the AI Center of Excellence by sharing best practices and mentoring others.

Requirements:

Education:

• Bachelor's degree with 5+ years of experience in designing, developing, and deploying machine learning models using Databricks, Azure ML, or Palantir.
• Master's degree with 3+ years of experience, or a Ph.D. in a relevant field such as Computer Science, Engineering, Data Science, or AI.

Experience:

• 5+ years of hands-on experience in AI/ML development and implementation, including 3+ years integrating LLM solutions with platforms like Databricks or Palantir.
• Experience in evaluating RAG Chat Bots using LLMs-as-a-Judge frameworks.
• Proven experience in observability, monitoring, and debugging AI/ML systems, especially in the context of LLMs.

Technical Skills:

• Proficiency in programming languages such as Python, R, or Java, with experience in libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Strong expertise in LLM architecture, training, and inference, with hands-on experience in pretraining, fine-tuning, and advanced techniques like RLHF, distillation, LoRA, and quantization.
• Experience in optimizing inference engines/servers and speculative decoding.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud for model deployment.

Additional Skills:

• Strong problem-solving abilities with attention to detail and adaptability in a fast-paced startup environment.
• Excellent communication and teamwork skills, with a focus on effective collaboration across various functions.
• Proactive and self-driven, with a strong sense of ownership over the systems you work on.
• Strong technical writing skills, able to create clear and concise documentation for a wide range of audiences.

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