Lead - ML Engineering

What's in it for you:

• Be part of a global enterprise and build AI solutions at scale.
• Work alongside a highly skilled and technically strong team.
• Contribute to solving high-complexity, high-impact challenges in data transformation and machine learning.

Responsibilities:

• Build production ready data acquisition and transformation pipelines from ideation to deployment.
• Being a hands-on problem solver and developer helping to extend and manage the data platforms.
• Apply best practices in data modeling and building ETL pipelines (streaming and batch) using cloud-native solutions
• Model development: Design, develop, and evaluate state-of-the-art machine learning models for information extraction, leveraging techniques from NLP, computer vision (if applicable), and other relevant domains.
• Data preprocessing and feature engineering: Develop robust pipelines for data cleaning, preprocessing, and feature engineering to prepare data for model training.
• Model training and evaluation: Train, tune, and evaluate machine learning models, ensuring high accuracy, efficiency, and scalability.
• Deployment and monitoring: Deploy and maintain machine learning models in a production environment, monitoring their performance and ensuring their reliability.
• Research and innovation: Stay up-to-date with the latest advancements in machine learning and NLP, and explore new techniques and technologies to improve the extraction process.
• Collaboration: Work closely with product managers, data scientists, and other engineers to understand project requirements and deliver effective solutions.
• Code quality and best practices: Ensure high code quality and adherence to best practices for software development.
• Communication: Effectively communicate technical concepts and project updates to both technical and non-technical audiences.

What We're Looking For:

• 6-10 years of professional software work experience, with a strong focus on Machine Learning, Natural Language Processing (NLP) for information extraction and MLOps
• Expertise in Python and related NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face)
• Experience with Apache Spark or other distributed computing frameworks for large-scale data processing.
• AWS/GCP Cloud expertise, particularly in deploying and scaling ML pipelines for NLP tasks.
• Solid understanding of the Machine Learning model lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring, specifically for information extraction models .
• Experience with CI/CD pipelines for ML models, including automated testing and deployment.
• Docker & Kubernetes experience for containerization and orchestration.
• OOP Design patterns, Test-Driven Development and Enterprise System design
• SQL (any variant, bonus if this is a big data variant)
• Linux OS (e.g. bash toolset and other utilities)
• Version control system experience with Git, GitHub, or Azure DevOps.
• Excellent Problem-solving, Code Review and Debugging skills
• Software craftsmanship, adherence to Agile principles and taking pride in writing good code
• Techniques to communicate change to non-technical people

Nice to have

• Core Java 17+, preferably Java 21+, and associated toolchain
• Apache Avro
• Apache Kafka

Other JVM based languages - e.g. Kotlin, Scala