Machine Learning Engineer

1 week ago


New Delhi, India Torry Harris Integration Solutions Full time

Job Description: We are seeking a talented and motivatedMachine Learning Engineerwith a focus onGenerative AIandMLOpsto join our dynamic team. The ideal candidate will design, develop, and deploy machine learning models, leveraging generative AI techniques and operational best practices. You will collaborate closely with data scientists, software engineers, and product teams to deliver scalable AI-driven solutions that enhance business outcomes and customer experiences.Key Responsibilities: Design, build, and optimizemachine learning and generative AI models , including model fine-tuning, embedding generation, and evaluation. Develop and maintainMLOps pipelinesfor model deployment, monitoring, retraining, and scaling across production environments. Implementdata preprocessing, feature extraction, labeling, and augmentationworkflows for robust model performance. Deploy and manage models incontainerized environmentsusingDockerandKubernetes , integrating withcloud AI services(AWS, Azure, or GCP). Collaborate with cross-functional teams to identify, prototype, and productionizeAI-driven solutionsaligned with business objectives. ConductA/B testing , monitor model drift and performance, and iterate model improvements. Implementdata versioning ,feature store management , andexperiment trackingto ensure reproducibility. Maintain comprehensive documentation for algorithms, data pipelines, and model lifecycle management. Stay current with advancements inmachine learning, generative AI , andMLOps practices .Skills and Tools Required: Solid foundation inPython ,NumPy ,Pandas ,Scikit-learn , andMatplotlibfor data analysis and model development. Strong hands-on experience withTensorFloworPyTorchfor ML/DL model development. Understanding ofAI model serving ,API exposure , andinference optimizationfor real-time predictions. Familiarity withMLOps principlesand tools such asMLflow ,Kubeflow , andDVCfor model orchestration and version control. Exposure toGenerative AItechniques, includingtransformer architectures ,GANs ,VAEs , andfine-tuningfor domain-specific tasks. Basic understanding ofRAG (Retrieval-Augmented Generation) pipelines ,vector databases , andsimilarity search mechanisms . Experience inA/B testing ,model monitoring , andcloud-based ML operations . Knowledge ofdata versioningandfeature store toolssuch asFeastorTecton . Familiarity withversion control systemslikeGitand CI/CD practices for ML workflows.Tools & Technologies: Machine Learning Frameworks:TensorFlow, PyTorch, Keras Data Processing Libraries:Pandas, NumPy, Scikit-learn Visualization Tools:Matplotlib, Seaborn MLOps Tools:MLflow, Kubeflow, DVC, Airflow Feature Stores & Data Versioning:Feast, Tecton Containerization & Orchestration:Docker, Kubernetes CI/CD & Automation:Jenkins, GitHub Actions Cloud Platforms:AWS, Azure, or GCP (AI/ML Services) Vector Databases:FAISS, Pinecone, Chroma (for embedding-based search)Preferred Qualifications: Experience working on projects involving Generative AI applications. Familiarity with containerization technologies like Docker and orchestration tools such as Kubernetes. Understanding of data privacy and ethical considerations in AI and machine learning.If you are passionate about leveraging machine learning to create innovative solutions and have a keen interest in Generative AI and MLOps, we encourage you to apply and join our forward-thinking team.Mandatory Skills AI ML Engineer, MLOps, Kubernetes



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