Note: The job is a remote job and is open to candidates in USA. Kadence is seeking a Lead Research Engineer who will leverage expertise in AI and ML to create innovative solutions for legal, accounting, and government professionals. The role involves providing technical leadership, developing scalable ML solutions, and collaborating with a global team to drive the company’s digital transformation.

Responsibilities

• Provide technical leadership partnering with other engineers to develop and improve methodology and evolve the technology stack by establishing standards and best practices that scale
• Applying modern software development practices, you will be involved in the entire software development lifecycle, building, testing and delivering high-quality solutions
• You will create large scale data processing pipelines to help researchers build and train novel machine learning algorithms
• You will develop high performing scalable systems in the context of large online delivery environments
• Working in a collaborative team-oriented environment, you will share information, value diverse ideas, partner with cross-functional and remote teams
• With a strong sense of urgency and a desire to work in a fast-paced, dynamic environment, you will deliver timely solutions
• You are empowered to try new approaches and learn new technologies. You will contribute innovative ideas, create solutions, and be accountable for end-to-end deliveries
• Through dynamic engagement and communication with cross-functional partners and team members, you will effectively articulate ideas and collaborate on technical developments

Skills

• A Bachelor of Science degree, computer science or related field
• At least 8 years of software engineering experience, ideally in the context of machine learning and natural language processing
• Experience leading technical workstreams within a software engineering organization
• Skilled and have a deep understanding of Python software development stacks and ecosystems, experience with other programming languages and ecosystems is ideal
• Driving innovation throughout the entire software lifecycle – specify, design, build, scale and maintain Machine Learning systems and capabilities in production environments
• Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn, PyTorch
• Take pride in writing clean, reusable, maintainable and well-tested code
• Experience in collaborating with research scientists to evaluate, prototype and productionize research concepts
• Proficiency in automation, system monitoring, and cloud-native applications, with familiarity in AWS or Azure (or a related cloud platform)
• Proficiency in system analysis and design & Consider DevOps and automation as fundamental pillars of your work
• A desire to learn and embrace new and emerging technology
• Familiarity with probabilistic models and an understanding of the mathematical concepts underlying machine learning methods
• Demonstrated ability to mentor engineers, elevate team technical practise
• Experience integrating Machine Learning solutions into production-grade software with a sound understanding of ModelOps and MLOps principles and the ability to translate between language and methodologies used both in research and engineering fields
• Previous exposure to Natural Language Processing (NLP) problems and familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, etc
• Hands-on experience in other programming and scripting languages (Java, TypeScript, JavaScript, etc.)

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