Engineering Manager - AI & ML

Job Description

As a senior engineering leader, your role will involve building and scaling AI/ML capabilities across digital and e-commerce platforms. You should be technically strong, hands-on, and experienced in leading teams to execute strategies effectively.**Key Responsibilities:**- Own the AI/ML roadmap for engineering, from solution design to production rollout.- Lead the development of AI/ML and GenAI solutions integrated with core platforms.- Design and review microservice architectures for high-traffic systems.- Ensure ML models are production-ready and reliable (deployment, monitoring, scaling, cost control).- Build and mentor senior engineers and ML teams, while staying involved in key technical decisions.- Collaborate closely with product and business teams to translate problems into practical, scalable solutions.**Qualifications:**- B.Tech or MCA in Computer Science or a related discipline.- 16 years of overall software engineering experience.- At least 6 years in senior leadership roles managing engineers and architects.- Proven track record of delivering AI/ML systems at scale.- Experience in e-commerce, food-tech, or large consumer platforms is a plus.**Required Skills:**- Hands-on experience with Machine learning and deep learning (neural networks, gradient boosting).- Proficiency in ranking and personalization, time-series modeling (forecasting, anomaly detection).- Knowledge of computer vision (image quality, menu/catalog intelligence, shelf-life).- Familiarity with embeddings and vector search, Real-time inference, and TensorFlow/PyTorch.- Experience with GenAI models (LLMs and vision-language models) for AI assistants.- Expertise in recommendation and understanding systems, document/invoice processing, MLOps / LLMOps, and scalable AI platform engineering.**Preferred Skills:**- Strong hands-on background in Java application development and microservices.- Experience in building distributed, event-driven systems.- Good working knowledge of cloud platforms (AWS preferred).- Understanding of system reliability, performance, and observability. As a senior engineering leader, your role will involve building and scaling AI/ML capabilities across digital and e-commerce platforms. You should be technically strong, hands-on, and experienced in leading teams to execute strategies effectively.**Key Responsibilities:**- Own the AI/ML roadmap for engineering, from solution design to production rollout.- Lead the development of AI/ML and GenAI solutions integrated with core platforms.- Design and review microservice architectures for high-traffic systems.- Ensure ML models are production-ready and reliable (deployment, monitoring, scaling, cost control).- Build and mentor senior engineers and ML teams, while staying involved in key technical decisions.- Collaborate closely with product and business teams to translate problems into practical, scalable solutions.**Qualifications:**- B.Tech or MCA in Computer Science or a related discipline.- 16 years of overall software engineering experience.- At least 6 years in senior leadership roles managing engineers and architects.- Proven track record of delivering AI/ML systems at scale.- Experience in e-commerce, food-tech, or large consumer platforms is a plus.**Required Skills:**- Hands-on experience with Machine learning and deep learning (neural networks, gradient boosting).- Proficiency in ranking and personalization, time-series modeling (forecasting, anomaly detection).- Knowledge of computer vision (image quality, menu/catalog intelligence, shelf-life).- Familiarity with embeddings and vector search, Real-time inference, and TensorFlow/PyTorch.- Experience with GenAI models (LLMs and vision-language models) for AI assistants.- Expertise in recommendation and understanding systems, document/invoice processing, MLOps / LLMOps, and scalable AI platform engineering.**Preferred Skills:**- Strong hands-on background in Java application development and microservices.- Experience in building distributed, event-driven systems.- Good working knowledge of cloud platforms (AWS preferred).- Understanding of system reliability, performance, and observability.

Keyskills :
Machine learningDeep learningNeural networksComputer visionDocument processingMicroservicesDistributed systemsAWSPerformanceGradient boostingRankingpersonalizationTimeseries modelingEmbeddingsvector searchRealtime inferenceTensorFlowPyTor