Staff Machine Learning Engineer

Staff Machine Learning Engineer

Requirements

• 10+ years of experience in machine learning with multiple models deployed in operational settings.
• PhD in Machine Learning, Computer Science, or other quantitative field.
• Strong proficiency with the latest Large Language Model (LLM) technologies.
• Expertise in one or more areas of machine learning, such as deep learning, reinforcement learning, probabilistic modeling, or optimization.
• Strong communication, collaboration, and coaching skills.
• High proficiency in a procedural programming language (e.g. Python).
• Ability to translate and apply cutting edge research into practical solutions.
• Strong leadership and mentorship abilities, with a passion for guiding and developing other team members.

Responsibilities

• Pioneer cutting-edge Document AI systems at the forefront of generative AI innovation, building next-generation models that go beyond traditional document processing to achieve human-level understanding of complex legal and medical documents, intelligently extract key entities and relationships, perform sophisticated multi-document reasoning, and generate contextually-aware documents that transform business workflows.
• Implement and advance technologies in: Information Extraction (using traditional ML, LLMs, and multi-modal LLMs for entity recognition, relationship extraction, and document structure understanding), Information Retrieval (query understanding, semantic search, hybrid retrieval architectures, and learning-to-rank models), Data Management (schema design, knowledge graphs, distributed data pipelines, and petabyte-scale processing), RAG (Retrieval-Augmented Generation) with advanced techniques like multi-hop reasoning, chain-of-thought prompting, and self-consistency checks, Prompt Engineering (few-shot learning, instruction tuning, and context window optimization), LLM fine-tuning (parameter-efficient techniques like LoRA/QLoRA, instruction fine-tuning, and domain adaptation).
• Own technical roadmaps and work closely with engineers, product managers, and other stakeholders to integrate research findings into scalable, production-ready solutions.
• Help set team best practices on how prompting experimentation and development is done; design and implement efficient procedures for benchmarking and optimizing prompt performance.
• Act as a strategic advisor for leaders across the organization on driving business impact through machine learning.
• Provide technical leadership and mentorship for a highly skilled team of data scientists and machine learning engineers, guiding them in solving complex business problems.
• Collaborate with domain experts (legal, healthcare, etc), product managers, and engineers to translate insights into robust machine learning systems.
• Create tools that empower internal teams and clients to make data-driven decisions.
• Mentor junior team members, promoting a culture of excellence and collaboration.

Preferred Qualifications

No preferred qualifications provided.