5 - 7 years

7 - 9 Lacs

Posted:11 hours ago| Platform: Naukri logo

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Job Description

Job Description

Job Title: AI/ML Solutions Engineer (Generative AI)

Experience Range: 5-7 Years

Location: Bangalore (Hybrid Mode)

Resillion, a leading quality engineering and digital assurance company with offices in the UK, Belgium, Netherlands, US, China & India, is seeking a highly skilled and experienced AI/ML Solutions Engineer with a specialization in Generative AI to join our innovative India team. This role will be instrumental in driving the development and implementation of cutting-edge generative AI solutions to address various quality assurance and cyber security use cases throughout the software development lifecycle.

Responsibilities:

  • Advise stakeholders on the potential and application of generative AI to address quality assurance and cyber security challenges across the software development lifecycle.
  • Architect and design scalable and robust generative AI solutions tailored to specific use cases in quality engineering and cyber security.
  • Lead the development and implementation of generative AI models and applications on both Microsoft Azure and Google Cloud Platform.
  • Develop and maintain efficient data pipelines and workflows for generative AI projects within Azure and GCP environments.
  • Collaborate with software development teams, quality engineers, and security experts to integrate generative AI solutions into existing processes and tools.
  • Design and implement experiments to evaluate the performance and effectiveness of generative AI models and applications.
  • Develop and deploy generative AI models into production environments on Azure and GCP, ensuring scalability, reliability, and security.
  • Monitor and maintain deployed generative AI solutions, addressing any issues and optimizing performance.
  • Research and evaluate new generative AI techniques and tools to identify opportunities for innovation and improvement.
  • Document generative AI solutions, including architecture, design, and implementation details.
  • Contribute to knowledge sharing and best practices within the team regarding generative AI development and deployment.

Qualifications
  • You possess a minimum of 5+ years of proven experience in developing and deploying Machine Learning models, with a strong emphasis on building and deploying Generative AI applications.
  • You have a deep understanding of generative AI techniques and models (e.g., GANs, VAEs, Transformers, diffusion models) and their application in real-world scenarios.
  • You have hands-on experience in the entire lifecycle of AI/ML solution development, with a focus on generative AI, from data exploration and preprocessing to model training, evaluation, deployment, and monitoring.
  • You have proven experience in designing, architecting, and implementing AI/ML solutions, with a focus on generative AI, within both the Microsoft Azure and Google Cloud Platform (GCP) ecosystems, leveraging their respective AI/ML services (e.g., Azure Machine Learning, Azure AI Services, Vertex AI, Google Cloud AI Platform).
  • You are proficient in programming languages relevant to generative AI development (e.g., Python) and deep learning frameworks (e.g., TensorFlow, PyTorch, Transformers).
  • You are adept at translating complex business requirements into innovative and practical generative AI solutions.
  • You possess excellent problem-solving skills and a passion for exploring and implementing the latest advancements in generative AI.
  • You are a strong communicator and collaborator, capable of effectively articulating technical concepts related to generative AI to both technical and non-technical stakeholders.
  • You are passionate about the potential of generative AI to revolutionize quality assurance and cyber security.
Bonus:
  • Experience with various Free and Open Source Software (FOSS) solutions relevant to AI/ML and generative AI development and deployment, such as:
  • ML/DL Frameworks: TensorFlow, PyTorch, scikit-learn, Keras, Hugging Face Transformers.
  • Data Science Libraries: Pandas, NumPy, Matplotlib, Seaborn.
  • MLOps Tools: MLflow, Kubeflow, Airflow.
  • Data Engineering Tools: Apache Spark, Apache Kafka, PostgreSQL, MySQL.
  • Containerization & Orchestration: Docker, Kubernetes.
  • Experience in applying generative AI to specific quality assurance domains (e.g., synthetic data generation for testing, AI-assisted test case generation).
  • Experience in applying generative AI to specific cyber security domains (e.g., AI-driven threat detection, generation of adversarial examples for security testing).
  • Familiarity with prompt engineering techniques for large language models (LLMs).
  • Understanding of ethical considerations and responsible AI development practices related to generative AI.

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