Job Description

We are looking for a data scientist with exceptional skills in Machine Learning (ML) and Artificial Intelligence (AI). We are seeking an experienced data scientist with a strong focus on building and maintaining sophisticated end to end pipelines using ML Ops. The successful candidate will possess a proven track record of designing, developing, and deploying successful innovative Generative AI (GenAI) software solutions. This role requires a proven communicator who effectively interfaces between technical and business teams, translating complex AI capabilities and technical insights into actionable business value.



Minimum Qualifications:


Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. 3+ years of experience building the production backend for AI/ML systems in Python, with proven expertise in creating scalable APIs using modern frameworks like FastAPI or Flask. Hands-on experience with one or more agentic frameworks such as RAG, Google ADK, LangChain, CrewAI, or LangGraph. 2+ years of hands-on experience with database systems (e.g., SQL, NoSQL) and designing scalable RESTful APIs. 2+ years of proven experience deploying and maintaining applications in a cloud-native environment, with a strong preference for GCP. 2+ years of experience with DevOps practices and tools such as Docker, Kubernetes, and Terraform. Proven experience architecting and implementing production-grade data ingestion pipelines for AI agents, including sophisticated strategies for data chunking, splitting, and generating embeddings at scale. Demonstrable experience using modren GCP products like GCS, Bigquery, Vertex AI, Postgres, Dataflow, EventArc, Cloud Run etc. Experience integrating and productionizing cloud-based AI tools, with a preference for Vertex AI. A genuine passion for exploring, evaluating, and integrating new technologies to drive business impact. A high degree of comfort working in ambiguous, fast-paced environments where you are empowered to innovate.
Preferred Qualifications:


Master's or PhD in Computer Science, AI, or a related field. 5+ years of advanced Python development experience, particularly with libraries like Pandas, PyTorch, and TensorFlow for NLP and deep learning. 3+ years of in-depth experience developing and deploying production-grade AI solutions on GCP or AWS. A portfolio of projects demonstrating the successful design and deployment of multi-agent systems or complex GenAI applications. Experience with the security considerations inherent in agentic systems, such as authentication and authorization between agents.

Architect, develop, and deploy end-to-end agentic Generative AI (GenAI) applications that solve complex real-world problems, with a specific focus on improving engineering challenges and inefficiencies. Design and implement robust, scalable data science and Machine Learning Operations (MLOps) pipelines primarily within any cloud environment (eg . Google Cloud Platform), ensuring efficient deployment and maintenance of AI solutions. Lead the integration of new cloud technologies and AI tools (e.g., Vertex AI) into our workflows, continuously evaluating their potential and articulating their business value to drive innovation and efficiency. Acquire a deep understanding of vehicle engineering problems, translating them into appropriate mathematical representations and AI/ML solutions (classification, prediction, intelligent automation). * Ensure the overall quality and integrity of data and solutions throughout the development lifecycle, from data collection and cleaning to model deployment.