Who You Are:

📍At least 6 years of experience as a Machine Learning or AI Engineer working with Python, JS/TS, Go, or similar languages. 📍Comfortable working with frameworks such as PyTorch, TensorFlow or similar frameworks and ecosystems. 📍Comfortable operating across cloud environments (AWS, GCP, Azure) and leveraging tools like Vertex AI, SageMaker, or Databricks. 📍Proven ability to architect, build, train, and deploy production-grade AI models. 📍Hands-on experience building or integrating AI-powered features (e.g., RAG, recommendation systems, semantic search, predictive analytics, etc.). 📍Strong understanding of machine learning and neural network architecture, including data preprocessing, model evaluation, and serving at scale. 📍Strong knowledge of MLOps/LLMOps best practices, including monitoring, CI/CD for ML, and production deployment. 📍Experience building and maintaining scalable data infrastructure (e.g. data pipelines, feature stores, and data lakes). 📍Strong understanding of software engineering fundamentals. 📍Track record of translating complex AI concepts into practical client solutions, ideally in consulting or fast-moving environments. 📍Proven experience working in a consulting or client-facing role with the ability to manage client expectations and timelines.

What You’ll Do:

📍Engage with clients to understand their problems, needs, goals, and technical environments. 📍Architect and build scalable AI systems from data ingestion to model training to serving and monitoring. 📍Apply best practices in MLOps or LLMOps, including testing, monitoring, and reliability. 📍Build and integrate AI services and APIs into applications, collaborating closely with product and full-stack teams. 📍Design and build scalable data pipelines and data lakes as needed. 📍Conduct experiments, analyze results, and iterate quickly to maximize model and system performance.

The future of finance is here — whether you’re interested in blockchain, cryptocurrency, or remote web3 jobs, there’s a perfect role waiting for you.