- Continuously monitor and evaluate emerging developments in artificial intelligence including advancements in foundational models generative AI multi-modal AI and agentic systems.
- Conduct structured research and experimentation to assess the performance feasibility and enterprise applicability of new AI models frameworks and architectures.
- Analyze competing technologies and approaches to determine optimal AI solutions and implementation strategies for business use cases.
- Develop research prototypes and proof-of-concepts to validate new AI capabilities before enterprise adoption.
- Provide technical recommendations and research insights to leadership and engineering teams regarding emerging AI opportunities.
- Translate research findings into practical guidance reference architecture and implementation frameworks for downstream teams.
- Collaborate with engineering data science and product teams to support the adoption of validated AI capabilities.
- Evaluate open-source and commercial AI ecosystems identifying tools models and platforms that can accelerate enterprise AI capabilities.
- Document research findings benchmarking results and architectural recommendations to support informed decision-making.
- Mentor junior researchers and contribute to building a strong internal knowledge base around evolving AI technologies.
Key Skills Required:
- Strong understanding of modern AI and machine learning techniques including large language models generative AI and emerging AI architectures.
- Ability to quickly analyze and understand new AI research papers frameworks and model releases and evaluate their practical relevance.
- Experience working with AI ecosystems such as Hugging Face Ollama OpenAI Anthropic or other foundational model platforms.
- Familiarity with LLM techniques such as prompt engineering RAG architecture fine-tuning approaches (LoRA QLoRA) and model evaluation frameworks.
- Strong logical reasoning and analytical skills to compare different AI approaches and recommend optimal solutions.
- Experience designing and running AI experiments benchmarking models and evaluating performance trade-offs.
- Understanding of AI system architecture model deployment considerations and integration patterns.
- Strong programming and experimentation skills in Python and common AI frameworks.
- Ability to clearly communicate complex AI concepts and research findings to both technical and non-technical stakeholders.
- Curiosity and passion for staying up to date with the rapidly evolving AI research and innovative landscape.
Qualifications :
- Bachelors degree or advanced degree (Masters or Ph.D.) in Computer Science Machine Learning Artificial Intelligence Mathematics Physics or a related quantitative discipline
- Minimum 5 years of professional experience in AI/ML research development or applied machine learning roles
- Proven track record of conducting rigorous AI research including experimentation design benchmarking and performance analysis
- Strong analytical and logical reasoning capabilities with the ability to critically assess competing AI technologies and architectures
- Exceptional written and verbal communication skills with proven ability to articulate sophisticated AI concepts to both technical and non-technical stakeholders
Remote Work :
No
Employment Type :
Full-time
Continuously monitor and evaluate emerging developments in artificial intelligence including advancements in foundational models generative AI multi-modal AI and agentic systems.Conduct structured research and experimentation to assess the performance feasibility and enterprise applicability of new ...
- Continuously monitor and evaluate emerging developments in artificial intelligence including advancements in foundational models generative AI multi-modal AI and agentic systems.
- Conduct structured research and experimentation to assess the performance feasibility and enterprise applicability of new AI models frameworks and architectures.
- Analyze competing technologies and approaches to determine optimal AI solutions and implementation strategies for business use cases.
- Develop research prototypes and proof-of-concepts to validate new AI capabilities before enterprise adoption.
- Provide technical recommendations and research insights to leadership and engineering teams regarding emerging AI opportunities.
- Translate research findings into practical guidance reference architecture and implementation frameworks for downstream teams.
- Collaborate with engineering data science and product teams to support the adoption of validated AI capabilities.
- Evaluate open-source and commercial AI ecosystems identifying tools models and platforms that can accelerate enterprise AI capabilities.
- Document research findings benchmarking results and architectural recommendations to support informed decision-making.
- Mentor junior researchers and contribute to building a strong internal knowledge base around evolving AI technologies.
Key Skills Required:
- Strong understanding of modern AI and machine learning techniques including large language models generative AI and emerging AI architectures.
- Ability to quickly analyze and understand new AI research papers frameworks and model releases and evaluate their practical relevance.
- Experience working with AI ecosystems such as Hugging Face Ollama OpenAI Anthropic or other foundational model platforms.
- Familiarity with LLM techniques such as prompt engineering RAG architecture fine-tuning approaches (LoRA QLoRA) and model evaluation frameworks.
- Strong logical reasoning and analytical skills to compare different AI approaches and recommend optimal solutions.
- Experience designing and running AI experiments benchmarking models and evaluating performance trade-offs.
- Understanding of AI system architecture model deployment considerations and integration patterns.
- Strong programming and experimentation skills in Python and common AI frameworks.
- Ability to clearly communicate complex AI concepts and research findings to both technical and non-technical stakeholders.
- Curiosity and passion for staying up to date with the rapidly evolving AI research and innovative landscape.
Qualifications :
- Bachelors degree or advanced degree (Masters or Ph.D.) in Computer Science Machine Learning Artificial Intelligence Mathematics Physics or a related quantitative discipline
- Minimum 5 years of professional experience in AI/ML research development or applied machine learning roles
- Proven track record of conducting rigorous AI research including experimentation design benchmarking and performance analysis
- Strong analytical and logical reasoning capabilities with the ability to critically assess competing AI technologies and architectures
- Exceptional written and verbal communication skills with proven ability to articulate sophisticated AI concepts to both technical and non-technical stakeholders
Remote Work :
No
Employment Type :
Full-time
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