Machine Learning Engineer

Designation: -ML / MLOPs EngineerLocation: -Noida (Sector- 132)Key Responsibilities:•Model Development & Algorithm Optimization : Design, implement, and optimizeMLmodels and algorithmsusing libraries and frameworks such asTensorFlow ,PyTorch , andscikit-learnto solve complex business problems.•Training & Evaluation : Train and evaluate models using historical data, ensuring accuracy,scalability, and efficiency while fine-tuning hyperparameters.•Data Preprocessing & Cleaning : Clean, preprocess, and transform raw data into a suitableformat for model training and evaluation, applying industry best practices to ensure dataquality.•Feature Engineering : Conduct feature engineering to extract meaningful features from datathat enhance model performance and improve predictive capabilities.•Model Deployment & Pipelines : Build end-to-end pipelines and workflows for deployingmachine learning models into production environments, leveragingAzure MachineLearningand containerization technologies likeDockerandKubernetes .•Production Deployment : Develop and deploy machine learning models to productionenvironments, ensuring scalability and reliability using tools such asAzure KubernetesService (AKS) .•End-to-End ML Lifecycle Automation : Automate the end-to-end machine learninglifecycle, including data ingestion, model training, deployment, and monitoring, ensuringseamless operations and faster model iteration.•Performance Optimization : Monitor and improveinference speedandlatencyto meet real-time processing requirements, ensuring efficient and scalable solutions.•NLP, CV, GenAI Programming : Work on machine learning projects involvingNaturalLanguage Processing (NLP) ,Computer Vision (CV) , andGenerative AI (GenAI) ,applying state-of-the-art techniques and frameworks to improve model performance.•Collaboration & CI/CD Integration : Collaborate with data scientists and engineers tointegrate ML models into production workflows, building and maintaining continuousintegration/continuous deployment (CI/CD) pipelines using tools likeAzure DevOps ,Git ,andJenkins .•Monitoring & Optimization : Continuously monitor the performance of deployed models,adjusting parameters and optimizing algorithms to improve accuracy and efficiency.•Security & Compliance : Ensure all machine learning models and processes adhere toindustrysecurity standardsandcompliance protocols , such asGDPRandHIPAA .•Documentation & Reporting : Document machine learning processes, models, and results toensure reproducibility and effective communication with stakeholders. Required Qualifications:• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a relatedfield.•3+ yearsof experience in machine learning operations (MLOps), cloud engineering, orsimilar roles.• Proficiency inPython , with hands-on experience using libraries such asTensorFlow ,PyTorch ,scikit-learn ,Pandas , andNumPy .• Strong experience withAzure Machine Learningservices, includingAzure ML Studio ,Azure Databricks , andAzure Kubernetes Service (AKS) .• Knowledge and experience in building end-to-end ML pipelines, deploying models, andautomating the machine learning lifecycle.• Expertise inDocker ,Kubernetes , andcontainer orchestrationfor deploying machinelearning models at scale.• Experience indata engineeringpractices and familiarity with cloud storage solutions likeAzure Blob StorageandAzure Data Lake .• Strong understanding ofNLP ,CV , orGenAIprogramming, along with the ability to applythese techniques to real-world business problems.• Experience withGit ,Azure DevOps , or similar tools to manage version control and CI/CDpipelines.• Solid experience inmachine learning algorithms ,model training ,evaluation , andhyperparameter tuning