Ai/ml engineer

3 weeks ago

Bangalore, India Tamcherry Full time

• Minimum 5 years of experience in machine learning engineering and AI development • Deep expertise in machine learning algorithms and techniques like supervised/unsupervised learning, deep learning, reinforcement learning, etc. • Solid experience in natural language processing (NLP) - language models, text generation, sentiment analysis, etc. • Proven understanding of generative AI concepts like text/image/audio synthesis, diffusion models, transformers, etc. • Expertise in Agentic AI and building real world applications using the same • Experience working with Agentic AI frameworks like Langgraph , ADK , Autogen etc. • Hands-on experience developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.)• Experience in MLOps and ML model deployment pipelines. • Proficiency in programming languages like Python, and ML frameworks like Tensor Flow, Py Torch, etc. • Knowledge of cloud platforms (AWS, GCP, Azure) and tools for scalable ML solution deployment • Experience with data processing, feature engineering, and model training on large datasets. • Familiarity with responsible AI practices, AI ethics, model governance and risk mitigation • Understanding of software engineering best practices and applying them to ML systems. • Experience with an agile development environment. • Exposure in tools/framework to monitor and analyse ML model performance and data accuracy. • Strong problem-solving, analytical, and communication abilities • Bachelor’s or master’s degree in computer science, AI, Statistics, Math or related fields Responsibilities: • Design, develop and optimize machine learning models for applications across different domains. • Build natural language processing pipelines for tasks like text generation, summarization, translation, etc. • Develop and deploy cutting-edge generative AI & Agentic AI applications • Implement MLOps practices - model training, evaluation, deployment, monitoring, and maintenance. • Integrate machine learning capabilities into existing products or build new AI-powered applications. • Perform data mining, cleaning, preparation, and augmentation for training robust ML models. • Collaborate with cross-functional teams to translate AI requirements into technical implementations. • Ensure model performance, scalability, reliability. • Continuously research and implement state-of-the-art AI/ML algorithms and techniques. • Manage the end-to-end ML lifecycle from data processing to production deployment.

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