Senior Software Engineer II
LexisNexisAbout the role
Responsibilities:
Collaborate with cross-functional teams to understand business requirements and translate them into robust, scalable AI-driven software solutions that bridge data science and production systems.
Design and implement complex software systems for ML/AI applications, following best practices in software architecture, coding standards, and design patterns while ensuring seamless integration between data science experiments and production environments.
Develop and maintain Python-based applications, libraries, and microservices using modern frameworks and tools, with a focus on transforming data science experiments into scalable production-ready AI services.
Build and optimize robust model serving pipelines that enable both offline model training and real-time inference, ensuring high availability and performance.
Automate end-to-end MLOps workflows and develop internal ML tools to streamline the machine learning lifecycle from experimentation to deployment.
Monitor production data quality, model versions, cloud costs, and security compliance while maintaining infrastructure that empowers the data science team.
Participate in code reviews, ensuring code quality, maintainability, and adherence to coding standards across both traditional software and ML pipeline codebases.
Mentor and guide junior developers and data scientists, fostering a culture of continuous learning and knowledge sharing in both software engineering and MLOps practices.
Contribute to the development and implementation of automated testing strategies, including unit, integration, and end-to-end testing for both traditional applications and ML systems.
Stay up to date with the latest trends, technologies, and best practices in the Python ecosystem, software engineering, and MLOps/AI infrastructure.
Requirements:
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent professional experience.
Minimum of 5 years of experience in software development, with a strong emphasis on Python programming.
Proficient in Python web frameworks such as Django, Flask, or FastAPI.
Solid understanding of object-oriented programming principles, design patterns, and software architecture.
Experience with relational databases and ORM frameworks like SQLAlchemy.
Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.
Knowledge of cloud platforms (e.g., AWS, Azure, or GCP) and their services.
Experience with version control systems, preferably Git as well as continuous integration/continuous deployment (CI/CD) practices.
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.
Passion for writing clean, maintainable, and well-documented code.
Preferred Qualifications:
Experience working with data scientists on cross functional teams
Experience with data analysis libraries like Pandas and NumPy.
Knowledge of asynchronous programming and event-driven architectures.
Familiarity with microservices architecture and RESTful API design.
Experience with agile software development methodologies.
Proficiency in integrating LangChain or similar frameworks to build modular AI workflows and applications.
Experience in developing prompt-based APIs and chaining tools for task-specific generative AI solutions.
Familiarity with retrieval-augmented generation (RAG) pipelines and their implementation in scalable software systems.
Hands-on experience with building conversational agents, including integrating chat models with third-party APIs and custom backends.
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