Tredence - Data Science Manager - Generative Artificial Intelligence Architect

We are looking for a Manager, Data Science GenAI to lead a team of data scientists and machine learning engineers in developing and deploying cutting-edge Generative AI solutions. You will work closely with cross-functional teams, including product, engineering, and business stakeholders, to drive innovation and implement AI-driven solutions that enhance customer experience and business performance.

Key Responsibilities

Leadership & Strategy:

- Lead and mentor a team of data scientists and ML engineers working on Generative AI projects.

- Develop the AI roadmap in alignment with business goals and drive innovation in Generative AI applications.

- Collaborate with senior leadership to define AI strategy and drive adoption across the organization.

Model Development & Deployment:

- Design, train, fine-tune, and deploy large language models (LLMs), diffusion models, and other Generative AI architectures.

- Develop and optimize LLM-based applications, including chatbots, text generation, summarization, and multimodal AI.

- Ensure AI models are production-ready, scalable, and cost-efficient.

Technical Excellence:

- Stay updated on the latest advancements in Generative AI, deep learning, NLP, and computer vision.

- Implement best practices for MLOps, model monitoring, and ethical AI.

- Leverage open-source frameworks (e.g., Hugging Face, LangChain, PyTorch, TensorFlow) and cloud-based AI services (e.g., AWS Bedrock, Azure OpenAI, Google Vertex AI).

Collaboration & Communication:

- Partner with product managers, engineers, and business teams to define AI-driven features.

- Communicate complex AI concepts to non-technical stakeholders and influence decision-making.

- Drive cross-functional initiatives to integrate AI capabilities into various products and workflows.

Qualifications & Experience

Education: Master's or Ph.D. in Computer Science, AI/ML, Data Science, or a related field.

Experience: 8+ years of experience in AI/ML, with at least 2 years in a managerial or leadership role.

Technical Expertise:

- Strong background in Generative AI, deep learning, NLP, and computer vision.

- Proficiency in Python, PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex.

- Experience with LLM fine-tuning, retrieval-augmented generation (RAG), and multimodal AI.

- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools (Kubeflow, MLflow, Weights & Biases).

Soft Skills:

- Strong leadership, problem-solving, and stakeholder management skills.

- Ability to mentor and develop data science teams.

- Excellent communication and business acumen.

Nice-to-Have:

- Experience with vector databases (Pinecone, FAISS, Weaviate).

- Background in reinforcement learning and AI safety.

- Contributions to open-source AI projects or research publications.