About this role
Accenture seeks an AI consultant and data scientist for client projects in the automotive and industrial sectors. The role applies machine learning, generative AI, agentic AI and autonomous systems to improve processes and decision-making. Listed locations are Bengaluru (Bangalore), Gurugram (Gurgaon), Hyderabad and Chennai; the position is full-time.
Responsibilities
- Develop, deploy and monitor production AI/ML models for predictive analytics, anomaly detection and process optimization.
- Apply generative models, such as GPT, Stable Diffusion and DALL·E, to content generation, documentation, code synthesis and intelligent assistants.
- Build agentic automation, self-learning agents and decision-support systems, and develop autonomous solutions for predictive maintenance, supply-chain optimization and robotic process automation.
- Work with structured and unstructured data, including IoT sensor readings, manufacturing logs and customer interactions. Fine-tune LLMs for business applications while supporting ethical and explainable AI use.
- Use model-operations and orchestration tools for deployment, monitoring and retraining. Collaborate with engineers, business analysts and domain experts, and keep current with generative AI, autonomous AI and multi-agent research.
Qualifications
- The detailed requirements state a minimum of 3–6 years in data science, machine learning or AI-related roles; the job header separately lists 5–10 years of experience.
- Bachelor’s or master’s degree in statistics, economics, mathematics, computer science or a related discipline with an excellent academic record, or an MBA from a top-tier university.
- Required skills include Python or R, generative AI, LLMs, RAG applications, and ML libraries or services such as Scikit-learn, TensorFlow, Torch, Lang Chain or the OpenAI API.
Preferred
Exposure to industrial or automotive firms or professional services; prior automotive or industrial experience is a plus, but candidates from other domains are welcome. Other desirable skills include Spark or Hadoop, explainability, bias detection, AI ethics, Edge AI deployment on embedded devices, reinforcement learning and AI-driven optimization.