ML Engineer Lead

3 weeks ago

New Delhi, India Hyrfast Full time

Machine Learning Engineer LeadHiring Machine Learning Engineer Lead for our client, which is a global digital engineering company specializing in data engineering, cloud solutions, and enterprise AI services.Python | PySpark | AWS | MLOpsLocation: Noida/Gurgaon/Indore/Bangalore/PuneExperience: 8-10 years | Full-timeAbout the RoleAre you passionate about building scalable AI/ML systems that make real-world impact?We’re looking for a Senior Machine Learning Engineer with strong expertise in Python, PySpark, and AWS to design and deploy data-driven solutions that power intelligent decision-making across our organization.You’ll work at the intersection of data engineering, data science, and MLOps — collaborating with cross-functional teams to build, deploy, and optimize production-grade machine learning systems at scale.What You’ll Do- Design, develop, and maintain feature and data pipelines using PySpark and AWS tools. - Collaborate with data scientists, engineers, and product teams to build scalable ML solutions from concept to deployment. - Leverage AWS services such as SageMaker, Bedrock, and Kendra for advanced AI model development and deployment. - Apply expertise in data science, statistics, and machine learning to create predictive and analytical models. - Implement MLOps practices — including model management, deployment, monitoring, and continuous improvement. - Conduct exploratory data analysis (EDA) and derive actionable insights for business outcomes. - Work on diverse ML domains including Time Series Forecasting, NLP, Image/Video Analytics, and Generative AI. - Drive innovation and knowledge sharing within the team, fostering a culture of continuous learning and experimentation.What We’re Looking For✅ Core Skills & Experience- 5+ years of experience in Python and PySpark development for feature/data pipelines. - Proven track record in AI/ML system development and MLOps implementation at scale. - Strong understanding of statistical modeling (e.g., multinomial logistic regression) and data science methodologies. - Hands-on experience with AWS cloud services (SageMaker, Bedrock, Kendra, etc.). - Deep knowledge of ML lifecycle: data collection, preparation, feature engineering, model management, deployment, and monitoring. - Proficiency in statistics (probability distributions, hypothesis testing) and model evaluation metrics. - Exposure to time series modeling, forecasting, NLP, and image/video analytics.✅ Bonus / Good to Have- Experience with Large Language Models (LLMs) and Generative AI. - Familiarity with LangChain, LLAMAIndex, and foundation model tuning. - Knowledge of Docker and Kubernetes for scalable ML deployments. - Experience with data augmentation, performance evaluation frameworks, and AI pipeline optimization.Why Join Us?Work on cutting-edge AI and Generative AI projects impacting real business outcomes.Collaborate with top-tier engineers, data scientists, and innovators.Grow your technical and leadership skills in a fast-paced, data-driven environment.Be part of a culture that values curiosity, creativity, and continuous learning.

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