Artificial Intelligence Engineer

3 days ago


Lucknow, India Quanto Neural Full time

Key Responsibilities1. Model Development & Optimization - Build, train, and fine-tune machine learning and deep learning models. - Implement NLP, computer vision, or recommendation systems depending on project needs. - Conduct feature engineering, data preprocessing, and experiment design. - Optimize model performance through hyperparameter tuning and algorithm improvements. 2. Data Engineering & Pipelines - Design and maintain scalable data pipelines for model training and inference. - Work with ETL processes, data warehousing, and big data frameworks (e.g., Spark, Kafka). - Ensure data quality, governance, and security. 3. AI Deployment & MLOps - Deploy models to production using cloud services (AWS/GCP/Azure). - Build CI/CD pipelines for ML workflows. - Monitor model performance and drift; manage retraining pipelines. 4. Software Engineering - Develop robust, production-grade code in Python, Java, or similar languages. - Implement APIs and microservices for model inference. - Collaborate closely with backend, frontend, and DevOps teams. 5. Research & Innovation - Evaluate emerging AI technologies, models, and frameworks. - Experiment with LLMs, generative AI, and new architectures. - Translate research prototypes into production-ready solutions. Required SkillsTechnical Skills - Proficiency in ML libraries and frameworks (TensorFlow, PyTorch, Scikit-learn). - Strong programming skills in Python (preferred), C++, or Java. - Experience with cloud platforms (AWS Sagemaker, GCP Vertex AI, Azure ML). - Familiarity with vector databases, embeddings, RAG pipelines, or LLM orchestration. - Knowledge of data structures, algorithms, and system design. - Understanding of MLOps tools (Kubeflow, MLFlow, Docker, Kubernetes). Soft Skills - Strong analytical and problem-solving abilities. - Ability to communicate complex technical concepts clearly. - Collaboration with cross-functional teams. - Adaptability in fast-paced environments. Education & Experience - Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering, or related field. - 2–5 years of experience with machine learning/AI development (for mid-level roles). - Experience working with large datasets and high-scale systems. Preferred (Good to Have) - Experience with generative AI (GPT, diffusion models, fine-tuning, prompt engineering). - Familiarity with LLM frameworks like LangChain, LlamaIndex, Haystack. - Understanding of model compression, quantization, distillation. - Experience with multi-modal AI or reinforcement learning.



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