AI/ML Team Lead

• Lead and manage a team of AI/ML engineers and data scientists, setting clear goals, providing mentorship, and promoting a collaborative and growth-focused culture.
• Foster innovation and create an environment that encourages creative problem-solving and the application of state-of-the-art machine learning techniques.
• Conduct performance reviews, provide feedback, and guide career development for team members.
• Promote a collaborative team environment by facilitating team meetings, brainstorming sessions, and knowledge-sharing activities.

• Architect and design AI/ML models for a variety of use cases, such as predictive analytics, natural language processing (NLP), computer vision, recommendation systems, and optimization problems.
• Collaborate with product managers and stakeholders to understand business requirements and translate them into effective AI/ML solutions.
• Oversee the entire machine learning pipeline, including data collection, preprocessing, feature engineering, model selection, evaluation, and deployment.
• Develop and implement AI/ML algorithms and integrate them into production systems to solve complex business problems and enhance the overall user experience.

• Monitor and maintain model performance, ensuring that the deployed models remain accurate and efficient over time.
• Evaluate and improve existing AI/ML models, identifying areas for optimization and implementing solutions to enhance performance (e.g., accuracy, speed, scalability).
• Lead the deployment and integration of machine learning models into production environments, working closely with DevOps and infrastructure teams.
• Implement best practices for model versioning, monitoring, and continuous integration/continuous deployment (CI/CD).

• Stay up-to-date with industry trends and cutting-edge research in AI/ML and related fields.
• Evaluate and prototype new AI/ML technologies, tools, and frameworks that could improve the company's offerings or solve business problems more efficiently.
• Publish research papers, participate in conferences, or collaborate with academia to stay at the forefront of AI research and development.

• Collaborate with cross-functional teams, such as engineering, product, and business teams, to ensure AI/ML solutions align with company objectives and technical requirements.
• Act as a key stakeholder in data strategy, ensuring that AI/ML initiatives are aligned with broader company goals and available data resources.
• Communicate complex AI/ML concepts to non-technical stakeholders in a clear, concise manner to support decision-making processes.

• Document AI/ML processes, methodologies, and algorithms for internal knowledge sharing and compliance purposes.
• Provide regular progress updates to senior leadership, highlighting key milestones, results, and challenges.
• Create comprehensive reports that include model performance analysis, business impact, and insights gained from AI projects.

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field.

• 5+ years of experience working in AI/ML development, with a proven track record of designing, deploying, and managing machine learning models and solutions.
• 2+ years of experience in a leadership or managerial role, overseeing a team of AI/ML engineers or data scientists, and driving projects to completion.
• Strong experience in modeling and designing machine learning solutions across various domains (e.g., NLP, computer vision, predictive analytics, etc.).
• Experience working with big data tools and frameworks (e.g., Hadoop, Spark, Kafka) and knowledge of handling large datasets for training models.

• Proficiency in machine learning frameworks and libraries such as TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, etc.
• Deep understanding of algorithms in supervised, unsupervised, and reinforcement learning, as well as optimization techniques.
• Strong knowledge of programming languages such as Python, R, Java, and SQL, with experience in writing production-ready code.
• Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying and managing ML models.
• Experience with containerization (Docker, Kubernetes) for deploying models and building scalable AI infrastructure.
• Experience with model deployment and scaling, using tools like MLflow, TensorFlow Serving, or other deployment frameworks.

• Excellent leadership and people management skills, with the ability to motivate and guide a team toward achieving common goals.
• Strong problem-solving and analytical skills, with the ability to approach complex technical challenges and derive creative solutions.
• Excellent communication skills, both written and verbal, with the ability to explain complex AI/ML concepts to non-technical stakeholders.
• Collaborative mindset, capable of working cross-functionally with engineering, product, and business teams.

• Familiarity with advanced deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformers, etc.
• Experience with AI/ML in production environments, understanding how to manage model lifecycle, retraining, and continuous model improvement.
• Experience in agile development environments, contributing to sprint planning, standups, and retrospectives.
• Experience in specific domains such as healthcare AI, financial technology, or security AI is a plus.

Futurism Technologies