The Role
Lead the design, development, productionization, and monitoring of generative AI and RAG solutions. Establish scalable MLOps pipelines, model governance, and deployment practices while ensuring reliability, security, compliance, and responsible AI. Provide technical leadership and mentorship, collaborate with engineering and business stakeholders, and evaluate emerging AI technologies to drive strategic organizational initiatives.
Summary Generated by Built In
Position Overview
We are seeking a highly skilled Lead Data Scientist with deep expertise in Generative AI, Retrieval-Augmented Generation (RAG), and productionizing advanced machine learning models. The ideal candidate will have strong experience in MLOps and ML Engineering, ensuring scalable, reliability, and secure deployment of AI solutions into production environments. This role requires both technical leadership and strategic vision to drive impactful AI initiatives across the organization.
Key Responsibilities
· AI Solution Development
o Design, build, and productionize advanced ML/AI models, including Generative AI and RAG-based architectures.
o Lead end-to-end model lifecycle: data preparation, feature engineering, training, evaluation, deployment, and monitoring.
· MLOps & ML Engineering
o Establish and optimize MLOps pipelines for continuous integration, deployment, and monitoring of ML models.
o Implement best practices for model governance, reproducibility, and scalability.
o Collaborate with engineering teams to ensure seamless integration of AI solutions into production systems.
· Leadership & Strategy
o Provide technical leadership and mentorship to data scientists and ML engineers.
o Partner with product and business stakeholders to translate complex AI concepts into actionable business value.
o Drive innovation by evaluating emerging AI technologies and frameworks.
· Operational Excellence
o Ensure AI models meet performance, reliability, and compliance standards.
o Develop monitoring frameworks for model drift, bias detection, and performance degradation.
o Champion responsible for AI practices and security-first approaches.
Required Skills & Experience
· Technical Expertise
o Proven experience in Generative AI (LLMs, diffusion models, transformers) and RAG pipelines.
o Strong background in MLOps (CI/CD for ML, model monitoring, orchestration tools like MLflow, Kubeflow, Airflow).
o Solid ML Engineering skills: Python, PyTorch/TensorFlow, distributed training, cloud platforms (AWS, Azure, GCP).
o Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval systems.
Skills Required
- Proven experience with Generative AI, including LLMs, diffusion models, and transformers
- Experience designing and implementing Retrieval-Augmented Generation pipelines
- Strong MLOps experience, including CI/CD for machine learning, model monitoring, and orchestration tools such as MLflow, Kubeflow, or Airflow
- Solid machine learning engineering skills
- Proficiency in Python
- Experience with PyTorch or TensorFlow
- Experience with distributed training
- Experience with cloud platforms including AWS, Azure, or GCP
- Experience with vector databases such as Pinecone, Weaviate, or FAISS
- Experience with retrieval systems
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Veltris – Innovate, Accelerate, Transform to enable technology-driven Enterprise, Business, and Industry transformations. We are a next generation technology services company specializing in developing products, platforms and solutions in Data & Artificial Intelligence (“Data/AI”), Engineering R&D (“ER&D”) and Digital Product Engineering Services (“PES”).
