Principal Applied Scientist

Responsibilities: • Provide strategic direction and technical leadership in applying machine learning/AI within the organization, aligned with company goals and challenges. • Influence the R& D roadmap based on deep industry understanding and business needs. • Drive innovation with novel solutions in the automotive industry, advancing applied science through the latest research implementation. • Act as a key liaison between R& D and stakeholders, ensuring technical alignment with business objectives. • Collaborate with cross-functional teams to define and integrate machine learning solutions into products and services. • Publish research in top conferences, advancing field knowledge. • Provide mentorship to applied scientists, ensuring project success. Contribute to team growth through training and collaborative projects. • Define metrics for model evaluation in offline and real-time settings. Quantify and communicate ML impact to executives, influencing decisions. • Champion ethical AI practices, ensuring compliance and standards. • Define best practices for ML model development, testing, validation, and monitoring. • Demonstrate data-driven business acumen and technical expertise across the development lifecycle. Maintain technical excellence in algorithm development and deployment. Requirements: • Bachelor's/Master's/PhD in Data Science, Mathematics, Operations Research, or a related field. The right candidate has a background in probability and statistics, applied mathematics, or computational science and a history of solving difficult problems with good business impact using a scientific approach. • Experience working with major ML algorithms and frameworks. • Significant experience in Data Science and Machine Learning with a strong proven track record in delivering positive business impact. • 12+ years of hands-on experience with analytics, data science, and big data in a business context. • Proficient in Machine Learning, Deep Learning and Explainable AI concepts with the ability to explain them clearly to non-technical audiences • Experienced in developing and adapting state-of-the-art models for specific business needs, demonstrating a track record of success in complex, cross-functional projects. • Utilizing Probability and Statistics to derive meaningful insights from data. • Proficient in deep learning frameworks like TensorFlow, Keras, and PyTorch, and utilizing computer vision (OpenCV) and natural language processing (spaCy) libraries. • Implementing deep learning techniques, particularly Neural Networks. • Applying both fundamental and advanced Natural Language Processing concepts. Implementing Computer Vision methodologies. • Experience with Large Language Models is a must. Should have fine-tuned LLM on domain dataset. • Utilizing Git for efficient code management and version control. • Leveraging cloud platforms such as Google Cloud Platform, Microsoft Azure, and Amazon Web Services. • Should be well versed with Design of Experiments. • Experience in programming with Python and SQL or similar languages. • Experience in distributed model training. • Proficient in data visualization and presentation, transforming complex analyses into actionable insights. • Experience with MLOps tools and frameworks (e. g., MLflow, Kubeflow, Airflow). • Experience using ML platforms such as Databricks and SageMaker. Preferred Qualifications: • Experience in Recommendation Engine, Natural Language Processing, Computer Vision. • Domain knowledge of the automotive industry. • Enjoys discovering and solving problems, proactively seeking clarification of requirements and direction, and being a self-starter who takes responsibility when required. • Familiarity with Spark. • Strong interpersonal, verbal, visual, and presentation skills; ability to communicate complex findings in a simple manner to executives. • Ability to work collaboratively across multiple products and application teams. • A willingness to learn, share, and improve.