Senior Data Scientist Engineer (AI Focus)

This position is as a full time position supporting the financial services/payments space. Please apply only if you have relevant experience and have valid work authorization.

About Blankfactor

At Blankfactor, we are dedicated to engineering impact. We build high-quality tech solutions for companies looking to innovate and grow—especially in fast-moving industries like payments, banking, capital markets, and life sciences.

With offices in the U.S., Colombia, and Bulgaria, we’re expanding rapidly and focused on delivering excellence through technology and collaboration. If you’re looking to join a global team that values learning, innovation, and real results, Blankfactor is the place for you.

Job Summary: We are seeking a highly skilled Senior Data Scientist Engineer with deep expertise in Artificial Intelligence (AI) and Machine Learning (ML). This role bridges data science, software engineering, and applied AI research, enabling the development of scalable, production-ready AI systems that drive real-world impact. The ideal candidate has strong foundations in statistics, machine learning, and deep learning, combined with hands-on experience in engineering robust data and model pipelines.

Key Responsibilities:

• AI/ML Development: Design, build, and optimize machine learning and deep learning models for tasks such as NLP, computer vision, recommender systems, and generative AI.
• End-to-End Deployment: Engineer data pipelines, training workflows, and model-serving infrastructure for scalable deployment in production environments.
• Research & Innovation: Stay current with emerging AI research and translate cutting-edge techniques into practical solutions that add business value.
• Data Strategy: Collaborate with data engineering teams to ensure availability, quality, and governance of large-scale structured and unstructured datasets.
• Cross-Functional Collaboration: Partner with product managers, engineers, and business stakeholders to align AI initiatives with organizational goals.
• Mentorship: Guide and mentor junior data scientists/engineers, promoting best practices in model development, coding, and MLOps.
• Performance Monitoring: Define success metrics, implement monitoring systems, and continuously evaluate model performance in production.

Required Qualifications:

• Education: Master’s or PhD in Computer Science, Data Science, Mathematics, or related field (or equivalent experience).
• Advanced proficiency in Python (preferred), R, or Scala.
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face).
• Strong knowledge of deep learning, generative AI, LLMs, and reinforcement learning.
• Familiarity with big data technologies (Spark, Hadoop, Databricks) and cloud platforms (AWS, GCP, Azure).
• Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes, CI/CD for ML).
• Analytical Skills: Strong background in statistics, probability, and experimental design.
• Engineering Skills: Ability to build production-ready pipelines and APIs for model deployment.
• Soft Skills: Strong communication, problem-solving, and leadership abilities.

Preferred Qualifications:

• Prior work in AI-driven products (e.g., conversational AI, recommender systems, generative AI).
• Contributions to open-source AI/ML projects or published research in recognized conferences/journals.
• Experience in high-growth technology environments.