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About the Role
Engineer to perform the design and development of advanced analytics, machine learning, and applied GenAI solutions that solve complex business problems across diverse client engagements.
Responsibilities
- Perform exploratory data analysis and hypothesis-driven modeling.
- Design, train, and validate machine learning models aligned with business objectives.
- Develop evaluation frameworks and define performance metrics.
- Prototype and validate GenAI use cases using LLMs and embeddings.
- Apply statistical rigor to experimentation and performance assessment.
- Communicate insights and recommendations to technical and business stakeholders.
- Collaborate with ML Engineers to productionize validated solutions.
Requirements
- 3+ years of applied data science experience in enterprise environments.
- Experience designing multiagent solutions, different generative frameworks, applying LLMs, embeddings, and prompt engineering techniques.
- Strong statistical and modeling background.
- Expertise in Python and ML libraries.
- Ability to translate business needs into analytical solutions.
- Experience working in consulting or client-facing contexts preferred.
- Experience on some of the clouds (AWS, Azure or GCP).
- Advanced English proficiency.
- Proven experience delivering GEN AI solutions in enterprise contexts.
- Strong statistical foundation and experimentation capability.
- Practical experience applying LLMs beyond theoretical exploration.
- Ability to connect analytical outcomes with measurable business impact.
Skills
- Python
- ML libraries
- LLMs
- embeddings
- prompt engineering techniques
- AWS
- Azure
- GCP
Experience Level
- 3+ years
Education Level
- Master's degree or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline.