Lead AI Engineer focused on developing cutting-edge AI/ML solutions tailored for after-sales operations. Guiding a team of AI engineers from ideation to deployment and continuous improvement.
Responsibilities
Lead, mentor, a team of AI engineers, fostering a collaborative and innovative environment.
Provide technical guidance and oversight throughout the AI solution development lifecycle.
Drive best practices in MLOps, model development, testing, and deployment.
Stay abreast of the latest advancements in AI/ML and recommend their application to relevant business challenges.
Design, build, and deploy end-to-end AI/ML models and systems that address critical after-sales service needs.
Develop robust, scalable, and production-ready code for AI applications.
Perform data exploration, feature engineering, model training, evaluation, and optimization.
Integrate AI solutions with existing enterprise systems and data pipelines.
Collaborate closely with product managers, data scientists, business stakeholders, and IT teams to understand requirements, define project scope, and deliver impactful AI solutions.
Translate complex business problems into well-defined AI/ML technical requirements and architectural designs.
Identify opportunities to leverage AI to improve efficiency, reduce costs, and enhance customer satisfaction in after-sales service.
Debug and troubleshoot complex AI systems and data issues.
Requirements
Doctorate / Bachelor's or Master's degree in Computer Science, Engineering, :Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.
5+ years of professional experience in Artificial Intelligence, Machine Learning, or Data Science roles.
2+ years of experience leading or mentoring a small team of engineers or data scientists.
Strong hands-on programming proficiency in Python (including libraries like TensorFlow, PyTorch, scikit-learn, pandas, numpy).
Demonstrated experience in designing, building, and deploying machine learning models into production environments.
Solid understanding of machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning) and their practical applications.
Experience with Natural Language Processing (NLP)/LLM/Gen AI techniques and tools.
Experience with cloud platforms (e.g., GCP, AWS, Azure) for AI/ML development and deployment.
Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, Docker, Kubernetes).
Knowledge of causal inference, reinforcement learning, or optimization techniques.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Familiarity with after-sales service operations, customer support systems, or automotive industry data.
Contributions to open-source projects or a strong portfolio of personal AI/ML projects.
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