Job Title

Role: AI/ML Principal Architect (Application) Experience: 12 Years Job Mode: 9:00 AM – 6:00 PM, 5 Days – WFO Work Location: Bharat Forge, Mundhwa, Pune Role Summary: Bharat Forge and Kalyani Group are developing AI products in manufacturing automation and for other applications. As the AI/ML Principal Architect , you will be responsible for leading AI/ML solution development across our manufacturing automation and product portfolios. This is a high-impact role requiring deep technical expertise, and leadership capabilities to bring innovative products to market. Core Responsibilities: AI/ML Solution Design & Development End-to-End Solution Design : Lead the design and development of end-to-end AI solutions, from data ingestion and processing to model selection, training, deployment and inference. Ensure that solutions are architected to meet performance, scalability, and reliability requirements. Algorithm Development: Guide teams to design and use rule-based or deterministic algorithms when needed, to solve problems accurately and efficiently. Use these algorithms to set clear boundaries for AI/ML models and improve the reliability of the overall solution. Model Selection & Optimization : Guide the team in selecting appropriate machine learning and deep learning models based on project requirements. Optimize model performance through hyper-parameter tuning and model compression. Develop solutions where AI results are explainable and transparent to gain stakeholder trust. Solution Deployment and Monitoring : Collaborate with infrastructure and security teams to deploy the solution on premise or in the cloud. Ensure the model parameters are kept updated through continuous training and evaluation of AI/ ML models on new data. Monitor and maintain performance in production by detecting drift and implementing automated retraining pipelines. Perform A/B testing and experimentation to evaluate feature improvement. Cross-Functional Collaboration & Leadership Collaborate with Engineering and Product Teams : Work closely with software engineering, data science, robotics, and hardware teams to ensure seamless integration of AI components. Provide architectural guidance and support to align efforts across teams. Technical Leadership & Mentorship : Mentor AI/ML engineers, data scientists, and junior architects on best practices in AI architecture, model development, and deployment. Foster a culture of innovation, technical excellence, and collaboration within the team. Stakeholder Engagement : Engage with stakeholders, including product managers, clients and senior leadership, to understand business requirements and translate them into technical specifications for AI/ML solutions. Required Qualifications: Education : Master's or Ph.D. in Computer Science, Data Science, Engineering, or a related field with a focus on AI/ML. Experience : 12+ years of industrial experience (PhD-level academic experience will be considered with a weight of 0.5) 5+ years of experience in AI/ML or allied fields (PhD-level academic experience will be considered with a weight of 0.5) 5+ years in an architectural or senior technical leadership role in industry. Proven track record of architecting and deploying AI/ML solutions, preferably within manufacturing, industrial automation, or a similar domain. Hands-on experience with a broad range of machine learning, deep learning, and data processing frameworks (e.g., TensorFlow, Keras, PyTorch, Apache Spark). Experience with ML tools and libraries such as scikit-learn, XGBoost, LightGBM, and Hugging Face Transformers. Technical Skills : Theoretical Expertise: Good understanding of applied mathematics basics relevant to AI/ML such as linear algebra, probability, and statistics. Allied fields such as signal processing, control theory and information theory will be considered as a special advantage, especially due to relevance to various AI problems in manufacturing. AI/ML Expertise : Deep understanding of supervised, unsupervised, reinforcement, and generative learning techniques, as well as expertise in model evaluation, tuning, and optimization. Programming Skills : Strong programming skills in Python, C/C++, or other relevant languages for AI and data processing. Data Engineering : Understanding of data pipeline design, storage solutions (Kafka,Hadoop, Snowflake) to train and evaluate AI/ ML models. Software Architecture : Good understanding of software design patterns, microservices architecture, and API design principles relevant to AI/ ML solutions. MLOps and DevOps : Good Understanding of MLOps practices and tools (MLflow, Kubeflow, DVC) for model versioning, experiment tracking, and automated deployment. Experience of working in environments with CI/CD pipelines and DevOps practices. CUDA and GPU Processing : Experience in deploying models on GPU acceleration using CUDA for model training and inference optimization. (Good to have.) Cloud and Edge Deployment : Experience in deploying AI models on cloud (AWS,Azure, GCP) and edge computing platforms. Understanding of distributed computing and containerization (Docker, Kubernetes). Database Technologies : Experience with both SQL and NoSQL databases. (At least one is necessary, both will be considered good to have.) Data Visualization : Familiarity with data visualization libraries and tools (Matplotlib, Seaborn, Plotly, Tableau) for effectively communicating insights from AI models. Managerial Skills Cross-Functional Communication : Strong ability to communicate complex AI concepts to non-technical stakeholders, including executives, clients, and regulatory bodies. Leadership, Mentorship, and Collaboration: Ability to lead, mentor and collaborate flexibly and as required for various projects. Ability to quickly and fluidly create and manage teams, tracking quickly changing requirements from stakeholders. Strategic Understanding: As AI/ML principal architect, you will be occasionally participating in strategic discussions, developing and expressing your opinion on feasibility of various projects and various alternatives from the technical and cost perspective. Continuous Learning : Demonstrated commitment to staying updated with the latest advancements in AI/ML, particularly those relevant to manufacturing and automation.