Lead Research Engineer

About the Role

Lead Research Engineer with expertise in AI and ML, building data‑driven capabilities that transform how legal, accounting, and government professionals work across the globe.

• Provide technical leadership, partnering with engineers to develop and improve methodology and evolve the technology stack by establishing scalable standards and best practices.
• Involve in the entire software development lifecycle, building, testing, and delivering high‑quality solutions using modern development practices.
• Create large‑scale data processing pipelines to help researchers build and train novel machine‑learning algorithms, developing high‑performing scalable systems for large online delivery environments.
• Collaborate in a team‑oriented environment, sharing information, valuing diverse ideas, and partnering with cross‑functional and remote teams.
• Deliver timely solutions in a fast‑paced, dynamic environment with a strong sense of urgency.
• Try new approaches and learn new technologies, contributing innovative ideas, creating solutions, and being accountable for end‑to‑end deliveries.
• Communicate effectively with cross‑functional partners and team members to articulate ideas and collaborate on technical developments.

• ABachelor of Science degree in Computer Science or related field.
• At least 8 years of software engineering experience, ideally in machine learning and natural language processing.
• Experience leading technical work streams within a software engineering organization.
• Deep understanding of Python software development stacks and ecosystems, with experience in other programming languages and ecosystems considered ideal.
• Ability to drive innovation throughout the entire software lifecycle—specify, design, build, scale, and maintain Machine Learning systems in production environments.
• Familiarity with the Python data science stack, including Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit‑learn, and PyTorch.
• Experience writing clean, reusable, maintainable, and well‑tested code.
• Experience collaborating with research scientists to evaluate, prototype, and product ionize research concepts.
• Proficiency in automation, system monitoring, and cloud‑native applications, with familiarity in AWS or Azure or related cloud platform.
• Proficiency in system analysis and design; consider Dev Ops and automation as fundamental pillars of your work.
• Desire to learn and embrace new and emerging technologies.
• Familiarity with probabilistic models and understanding of mathematical concepts underlying machine learning methods.
• Demonstrated ability to mentor engineers and elevate team technical practice.
• Experience integrating Machine Learning solutions into production‑grade software with strong understanding of Model Ops and MLOps principles and ability to translate between research and engineering language and methodologies.
• Previous exposure to Natural Language Processing (NLP) problems and familiarity with key tasks such as Named Entity Recognition, Information Extraction, and Information Retrieval.
• Hands‑on experience in other programming and scripting languages (Java, Type Script, JavaScript, etc.).

• Hybrid Work Model: flexible hybrid working environment (2–3 days a week in the office depending on the role).
• Flexibility & Work‑Life Balance: supportive policies for caring for family, community, or personal time, including up to 8 weeks of work from anywhere per year.
• Career Development and Growth: learning and skill‑building programs to tackle emerging challenges and lead in AI.
• Industry Competitive Benefits: comprehensive benefit plans including flexible vacation, mental‑health days off, Headspace app access, retirement savings, tuition reimbursement, and wellness resources.
• Culture: inclusive,…