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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and implementing generative AI solutions, utilizing advanced techniques such as Language Models and deep learning frameworks. Proficient in data engineering practices, ensuring compliance with ethical standards and effective collaboration with stakeholders.
Highest-signal resume keywords
Generative AI TechniquesMachine Learning ExpertisePython ProgrammingData Engineering SkillsCloud Platform Experience
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningGenerative AINatural Language ProcessingData CurationData CleaningModel DeploymentSimilarity Search AlgorithmsTransfer LearningDomain Adaptation
Soft Skills
Problem-SolvingAnalytical SkillsCollaborationCommunicationInterpersonal Skills
Tools & Technologies
PythonRTensorFlowPyTorchAzureAWSGCPRedisHugging Face TransformersBERT
Industry Keywords
AI SolutionsData PrivacyEthical AIEnterprise Use CasesCloud Environment
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