Job Description

Position: AI Engineer – Data Conversion (Remote Opportunity) Experience: 5–7+ Years Location: Remote (Work from Anywhere) We're looking for an experienced AI Engineer to join our team and drive innovation in automating and enhancing our data conversion processes. This is a remote opportunity , allowing you to contribute from wherever you're most productive, while supporting sustainable and flexible work practices. What You Will Do: Research & Innovation: Stay current with the latest advancements in AI technologies, tools, and trends to continually improve and innovate our data conversion workflows. AI Model Development: Design and implement AI-driven solutions to automate and optimize core data conversion processes. Data Handling: Manage large datasets while ensuring data security, integrity, and privacy throughout the conversion pipeline. Secure Compliance: Build and deploy AI solutions that align with information security protocols and industry compliance standards. Testing & Validation: Rigorously test and validate AI models to ensure high accuracy, reliability, and performance. Documentation: Maintain clear and comprehensive documentation of methodologies, models, and deployment procedures. Performance Optimization: Monitor and enhance the performance of deployed AI models, including data aggregation and application scoring. Team Collaboration: Collaborate with cross-functional teams—data scientists, software engineers, and business analysts—to build scalable, integrated AI solutions. What You Will Need: Programming Expertise: Proficiency in Python, JavaScript/Node.js, and .NET Framework/Core (C#). ML Frameworks: Hands-on experience with TensorFlow, PyTorch, Keras, Scikit-Learn, and other machine learning libraries. Data Processing: Strong skills in data manipulation and analysis using tools like Pandas and NumPy, including handling unstructured data. Deep Learning Knowledge: Understanding of CNNs, RNNs, Transformers for tasks like NLP, image recognition, and more. Software Development Practices: Familiarity with agile methodologies, version control (Git), and DevOps workflows. Cloud Proficiency: Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying AI solutions. System Design: Ability to architect scalable systems using APIs and microservices for AI integration. Analytical Thinking: Strong problem-solving skills and the ability to troubleshoot and adapt AI solutions effectively. Collaborative Mindset: Experience working with cross-functional teams to align AI solutions with business goals. Nice to Have: Experience in the Financial Services Industry and knowledge of compliance regulations. Certifications in AI/ML or related technologies. Familiarity with reporting tools such as Splunk, SSRS, Cognos, or Power BI. Show more Show less