Machine Learning Specialist

We are seeking a versatile Machine Learning Specialist to own the end-to-end lifecycle of AI development. This role is designed for a technical expert who can navigate the entire spectrum of machine learning—from conducting state-of-the-art research and fine-tuning foundational models to architecting the production-grade pipelines and APIs that bring these models to life. You will bridge the gap between theoretical innovation and scalable business impact, ensuring our AI solutions are both cutting-edge and operationally robust.

Key responsibilities

• Conduct deep-dive research into state-of-the-art (SOTA) architectures and foundational models to solve complex business problems like credit scoring, fraud detection, and personalization.

• Execute rigorous hyperparameter tuning and fine-tuning techniques (e.g., PEFT, LoRA, QLoRA) to maximize model accuracy and efficiency.

• Develop comprehensive evaluation frameworks and leaderboards to monitor model accuracy and compare experimental iterations.

• Lead the design of experimentation datasets and production data pipelines, focusing on feature engineering and data augmentation.

• Ensure high-quality data inputs for both training and real-time inference, collaborating with data squads to maintain data integrity.

• Architect and manage the end-to-end deployment of models using containers (Docker, Kubernetes) and CI/CD pipelines.

• Build robust APIs to integrate AI models with internal platforms and refactor research code into production-grade, low-latency, and high-throughput codebases.

• Implement MLOps best practices, including versioning (DVC), drift detection, and automated quality gates to ensure alignment with internal KPIs and regulatory standards.

• Work as a core member of a cross-functional squad, aligning daily with Data Engineers, Backend Developers, and Product Owners to ensure seamless product integration.

• Author and maintain the full technical stack documentation, ranging from scientific research findings and experimental logs to system architecture diagrams and deployment guides.

• 3+ years in a functionally similar role (Data Science, ML Research, or ML Engineering).

• Expert-level Python and SQL.

• Strong experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX).

• Hands-on experience with Git, CI/CD, and MLOps tools.

• A strong bias toward model explainability and security.

• Demonstrable portfolio of advanced AI use cases (e.g., GenAI, NLP, Recommender Systems, or Graph Algorithms) preferred.

• Familiarity with AWS, GCP, or Azure AI services preferred.

• Published research in relevant AI/ML conferences or journals preferred.