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.
Responsibilities
- 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.
- Design, Implement and maintain production-grade MCP servers handling real user traffic at scale., ensuring robust authentication, rate-limiting, tooling integrations and comprehensive observability.
Qualifications
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.
