Machine Learning

3 days ago

Bengaluru, Karnataka, India AKIRA Insights Full time

DescriptionWe are looking for a highly skilled Machine Learning & GenAI Engineer with 45 years of hands-onTotal Experienceexperience in building ML models. The ideal candidate should be capable of independently designing PoCs, implementing MLOps pipelines, integratingng LLMs and converting prototypes into scalable product on systems. This role is part of our AI Center of Excellence, focusing on innovation, rapid prototyping, and enterprise-ready solution Description :4 to 5 years of hands-on experience in Machine Learning Engineering, AI Engineering, or MLOps.Domain ExperienceProven experience in building and deploying at least 2 end-to-end ML/AI solutions in a production AI :Practical, hands-on experience with Generative AI and Agentic AI frameworks is highly preferred.Education :Bachelor's or Master's degree in Computer Science/Data Science/AI.Mandatory SkillsProgramming: Expert proficiency in Python (including libraries like NumPy, Pandas, Scikit-learn).ML/DL Frameworks: Hands-on experience with PyTorch or TensorFlow (and Keras).Generative AI: Experience with LLMs (e.g., OpenAI, Gemini, Llama) and core concepts likeembeddings, tokenization, and fine-tuning.Agentic Frameworks: Proven experience with at least one Agent Orchestration Framework(e.g., LangChain, LangGraph, AutoGen).MLOps Tools: Practical experience with key MLOps components: Docker, Kubernetes, and anMLOps platform/tool (e.g., MLflow, Kubeflow, DVC).Cloud Platform: Proficiency in deploying and managing AI/ML workloads on a major cloudplatform (Databricks, AWS SageMaker, Google Cloud Vertex AI, or Azure ML).Databases: Strong knowledge of SQL and experience with Vector Databases (e.g., Familiarity with data engineering (Spark, SQL, ETL pipelines).Good To Have SkillsAdvanced MLOps: Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions) andsophisticated monitoring tools (Prometheus, Grafana, Datadog).Big Data: Familiarity with distributed computing frameworks like Apache Spark.Front-End Integration: Experience with creating APIs (FastAPI, Flask) and integrating MLservices with front-end applications.Other AI: Experience with Computer Vision or Time-Series Analysis in a production setting.Soft Skills: Strong communication skills for CoE evangelism, cross-functional collaboration, andpresenting POC results to stakeholders.Experience with RAG ArchitecturesExposure to Databricks Unity Catalog, DLT, Delta Live Tables, AutoML, FeatureStoresUnderstanding of security, compliance & responsible AI prac>ces.)

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