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Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformNoSQLPythonPyTorchRedisTensorflow
About the role
Key responsibilities & impact- Contribute to the design and implementation of state-of-the-art AI solutions
- Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI
- Collaborate with stakeholders to identify business opportunities and define AI project goals
- Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges
- Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases
- Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities
- Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment
- Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs
- Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs
- Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly
- Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency
- Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases
- Ensure compliance with data privacy, security, and ethical considerations in AI applications
- Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
Requirements
What you’ll need- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- Minimum 8-11 years of experience in Data Science and Machine Learning
- In-depth knowledge of machine learning, deep learning, and generative AI techniques
- Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch
- Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models
- Familiarity with computer vision techniques for image recognition, object detection, or image generation
- Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment
- Expertise in data engineering, including data curation, cleaning, and preprocessing
- Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems
- Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models
- Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions
- Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels
- Understanding of data privacy, security, and ethical considerations in AI applications
- Track record of driving innovation and staying updated with the latest AI research and advancements.
Benefits
Comp & perks- Competitive salary
- Flexible working hours
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Machine LearningDeep LearningGenerative AINatural Language ProcessingData CurationData CleaningModel DeploymentSimilarity Search AlgorithmsTransfer LearningDomain Adaptation
Soft Skills
Problem-SolvingAnalytical SkillsCollaborationCommunicationInterpersonal Skills