AI-ML Tech Engineer

8 - 13 years

16 - 20 Lacs

Posted:1 week ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Project description New settlements and confirmation system for FX trades. Responsibilities
We are seeking an AI-ML Tech Engineer who has a minimum of 8+ years of strong background in machine learning, data science, and software engineering. As a Machine Learning Engineer, you will develop and deploy machine learning models, work with large datasets, and collaborate with cross-functional teams to solve real-world problems. Skills Must have Proficient in building ML (Machine Learning) & NLP (Natural Language Processing) solutions using common ML libraries and frameworks. Proficient with Python language and worked on various ML toolkits like TensorFlow, PyTorch, Keras, Scikit Learn. Theoretical understanding of statistical models such as regression, clustering, and ML algorithms such as decision trees, Random Forests, neural networks, etc. Strong understanding of cloud computing and cloud AI services. Experience in deploying AI/ML models in production environments. Experience in data analytics, feature creation, model selection and ensemble methods, performance metrics and visualization. Experience working with large datasets and distributed computing systems. Experience in fine-tuning DL models including LLMs, SLMs. Knowledge of large language models from OpenAI such as GPT 3.5,GPT 4,C odex etc. Experience with Vector Stores and RAG pipelines. Proficient with Data-Modelling Tools. Proficient with multiple ML deployment strategies including static and dynamic. Excellent knowledge of CI, CD Pipelines for ML algorithms, training, prediction pipelines. Experience in translating ML-based outcomes to business-digestible insights. Excellent communication skills and experience in managing stakeholders at various levels. Nice to have Knowledge of ML Ops like continuous integration, continuous deployment. Knowledge of full stack development. Knowledge of Databricks, Data Mesh. Knowledge of ETL (Extract, Transform, Load) pipeline. Familiarity with agile methodologies, such as Scrum or Kanban, and project management tools such as JIRA/GITLAB. Experience with frameworks like flask/Django. Knowledge of Docker containers.

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