Senior Staff Applied Scientist @ Bangalore

Job Description

Key Responsibilities Provide strategic direction and technical leadership in applying machine learning/ AI within the organization, aligned with company goals and challenges. Influence R&D roadmap based on deep industry understanding and business needs. Drive innovation with novel solutions in the automotive industry, advancing applied science through 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 development lifecycle. Maintain technical excellence in algorithm development and deployment. Required Qualifications Bachelors/ Masters / PhD in Data Science, Mathematics, Operations Research or 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. 11+ years of hands-on experience with analytics, data science and big data experience 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 automotive industry. Enjoys discovering and solving problems; proactively seeking clarification of requirements and direction; 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.