Machine Learning Engineer

Greetings From Right Move !!!!!!! Please see below the Job Description. If you find this interesting and in line with your career aspirations, kindly revert to this email with your confirmation & updated CV. Experience – 7+ Years. Role – AI/ML Engineer. Job Type - Permanent. Mode – Work from Office. Company Location - Pune, Bhosari. Skill Set - AI/ML, MLOPS, Cloud, Python, Traditional AI,ML Algorithms, TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, LightGBM, and CatBoost. About Company: The AI COE (Centre of Excellence) where their central team of experts dedicated to accelerating the adoption of artificial intelligence and machine learning across the organization. The AI COE is responsible for making a business impact across the group of companies adding value chain—including Manufacturing, Supply Chain, R&D, Sales, Marketing, and Security—and is also responsible for AI governance. We partner with various business units to identify high-impact use cases, develop cutting-edge AI/ML solutions, and build and deploy them through Applied AI and innovation to deliver a strong ROI. Our focus is on fostering innovation, establishing best practices, and enabling the digital transformation of our operations, particularly within all Automotive sectors. Job Description: We are seeking a highly experienced and senior Machine Learning Engineer to join our AI COE in Pune. You will be responsible for the hands-on design, development, and deployment of advanced machine learning and deep learning models for our Manufacturing, R&D, Design, Sales & Marketing, and "Plants AI" initiatives. You will leverage your deep technical expertise to solve complex challenges in areas such as predictive maintenance, supply chain optimization, customer analytics, and process automation. A critical part of this role will be your proven ability to optimize and manage the entire lifecycle of ML models in production, especially for real-time performance on edge devices. Required Skills ● Advanced degrees (M.E, M.Tech) in Engineering, Computer Science, Statistics, or related fields with specialization in machine learning or AI are highly preferred. A Bachelor's of Engineering (B.E) is the minimum requirement. ● A minimum of 7 years of demonstrable, hands-on execution experience covering the full AI/ML lifecycle, including ML algorithm development, model development, deployment, and optimization in production environments. ● Direct experience working within a production or manufacturing environment, with a deep understanding of the unique challenges, operational constraints, and industrial settings. ● Proven ability in technical project management, with demonstrated success leading cross-functional teams and managing projects from inception to deployment. ● Strong programming skills in Python and C++, with Python being strongly preferred. Experience in software development for engineering applications and familiarity with version control systems like Git or TFS are also required. ● Deep familiarity with a wide range of machine learning frameworks and libraries, such as TensorFlow, PyTorch, Keras, Scikit-learn, XGBoost, LightGBM, and CatBoost. Required Qualifications & Skills: ● Core Machine Learning & AI: Deep proficiency in a wide range of ML and AI technologies. ● ML Algorithms: Extensive hands-on experience with supervised learning (e.g., SVM, Random Forests), gradient boosting (XGBoost, LightGBM, CatBoost), and unsupervised learning (e.g., K-Means, PCA, Isolation Forest). ● Deep Learning Architectures: In-depth knowledge of convolutional neural networks (CNNs), recurrent neural networks (RNNs), LSTMs, Transformers, and Generative Adversarial Networks (GANs). ● LLM and Generative AI: Strong familiarity with the architecture and application of Large Language Models (LLMs), including hands-on experience with popular open-source LLMs (e.g., Llama, Mistral, Falcon, Gemma families). Experience with fine-tuning, prompt engineering, and Retrieval-Augmented Generation (RAG) is highly desirable. ● AI for Design: Experience or strong interest in applying AI techniques to design processes, such as AI for CAS (Computer-Aided Styling) or CAD (Computer-Aided Design), is a significant plus. Cloud ML & Edge Computing: ● Cloud ML Engineering: Extensive hands-on experience with the ML services of major cloud providers, such as AWS SageMaker, Azure Machine Learning, Google Cloud AI Platform (Vertex AI), and OCI AI Services. Proven ability to train, optimize, and deploy large-scale machine learning models in a cloud environment. ● MLOps, LLMOps, & AIOps: Solid understanding and practical, hands-on experience with MLOps principles for building robust CI/CD pipelines, model/data versioning, monitoring, and governance. Knowledge of AI governance principles and security frameworks is essential. ● Edge Optimization: Demonstrated expertise in optimizing ML models for edge devices. This includes hands-on experience with quantization (INT8, FP16), pruning, knowledge distillation, and using runtimes like NVIDIA TensorRT, Qualcomm SNPE, Intel's OpenVINO, TensorFlow Lite, and ONNX Runtime. *We are looking for candidates who can join us within 30 days* If you find this interesting and inline with your career aspiration, please share your CV on or call on Thanks & Regards, Aishwarya D

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