AI/ML Architect

Key Responsibilities

• Strategic Leadership: Define and articulate the AI/ML vision and strategy for the company, ensuring alignment with overall business goals. Identify new opportunities to leverage AI/ML to drive innovation, efficiency, and revenue growth.
• Team Management & Mentorship: Lead, mentor, and grow a high-performing team of data scientists and machine learning engineers. Foster a culture of collaboration, innovation, and continuous learning. Provide technical guidance and career development support to team members.
• End-to-End Project Ownership: Oversee the entire lifecycle of AI/ML projects, from ideation and requirements gathering to model development, deployment, and monitoring. Ensure projects are delivered on time, within budget, and to the highest quality standards.
• Technical Architecture & Development: Provide hands-on technical leadership in the design and architecture of scalable and production-ready AI/ML solutions. Stay current with the latest advancements in the field and guide the team in adopting best practices for model development, MLOps, and data governance.
• Cross-Functional Collaboration: Work closely with product managers, software engineers, and business stakeholders to identify and prioritize AI/ML use cases. Effectively communicate complex technical concepts and project outcomes to both technical and non-technical audiences.
• Model Governance & Ethics: Establish and enforce standards for model validation, performance monitoring, and ethical AI. Ensure our models are fair, transparent, and compliant with relevant regulations.

Required Skills & Qualifications

• Educational Background: Degree in Computer Science or Maths, Artificial Intelligence, Statistics, or a related quantitative field.
• Professional Experience: A minimum of 10 years of professional experience in data science and machine learning, with at least 3-4 years in a leadership or management capacity.
• Proven Expertise: Demonstrated experience in developing and deploying a wide range of machine learning models, including but not limited to deep learning (CNNs, RNNs, Transformers), natural language processing (NLP), computer vision, and reinforcement learning.
• Technical Proficiency:
• Expert-level programming skills in Python.
• Extensive experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Strong experience with cloud platforms (AWS, Azure, or GCP) and their respective ML services (e.g., SageMaker, Azure ML, Vertex AI).
• Solid understanding of MLOps principles and tools (e.g., MLflow, Kubeflow, Docker, Kubernetes).
• Proficiency in data manipulation and analysis using SQL and libraries like Pandas and NumPy.
• Leadership Acumen: Proven ability to lead and inspire technical teams. Excellent project management, communication, and interpersonal skills.

Preferred

• A portfolio of patents or publications in reputable AI/ML journals or conferences.
• Experience working in a fast-paced, agile environment.
• Familiarity with big data technologies like Apache Spark or Hadoop.
• Experience with building and scaling AI solutions for [mention your specific industry, e.g., FinTech, Healthcare, E-commerce].