Lead Applied AI Scientist - Remote Role at AlgoLand

About the Role

We are seeking a Lead Applied AI Scientist to drive the design, development, and deployment of AI solutions at scale. This fully remote role combines deep technical expertise with system-level thinking and product impact. As a Lead Applied AI Scientist, you will lead end-to-end AI initiatives—from problem framing and modeling to deployment and continuous optimization—across a range of use cases including predictive modeling, optimization, and LLM-based systems.

What You'll Do

• Lead the design and implementation of advanced AI models across various domains such as forecasting, optimization, classification, and recommendation.
• Architect scalable AI pipelines, from data ingestion to model serving, ensuring robust performance and reliability.
• Apply statistical modeling, machine learning, and deep learning techniques to solve complex business problems.
• Design and deploy LLM-based solutions, including RAG pipelines, fine-tuning, and prompt engineering.
• Evaluate and optimize LLM performance, focusing on latency, accuracy, and cost-effectiveness.
• Lead the deployment of AI models into production environments at scale, defining and implementing MLOps best practices.
• Provide technical direction and mentorship to AI scientists and engineers, establishing standards for model development and evaluation.
• Collaborate with business stakeholders to define AI use cases and expected impact, communicating complex AI concepts clearly to non-technical audiences.

Requirements

• Advanced degree (Master’s or PhD) in Computer Science, Data Science, Applied Mathematics, or a related field.
• 6–10+ years of experience in applied AI/machine learning roles, with demonstrated production impact.
• Strong expertise in machine learning and statistical modeling, with proven experience deploying AI models into production at scale.
• Proficient programming skills in Python; familiarity with modern data and ML ecosystems such as MLflow, Docker, Kubernetes, and cloud platforms.
• Solid understanding of model evaluation, validation, and performance monitoring.

Nice to Have

• Experience with LLMs and Generative AI systems.
• Familiarity with distributed systems and high-scale data pipelines.
• Exposure to multiple industries (retail, telecom, finance, etc.).

What We Offer

• Opportunity to work on high-impact AI problems across industries.
• Exposure to cutting-edge AI technologies, including LLMs and advanced optimization.
• A culture of technical excellence and continuous learning.
• Flexible remote work environment with global collaboration.
• Competitive compensation aligned with experience and impact.