Transform the latest breakthroughs in large language models (LLMs), retrieval-augmented generation (RAG), and agentic AI into high-impact product capabilities.
Requirements
- Proven track record of shipping products or features that leverage LLMs, generative AI, or other large-scale machine-learning models.
- Expert-level Python programming skills and hands-on experience with modern ML frameworks.
- Practical experience with cloud environments (AWS, GCP, or Azure) and big-data technologies (e.g., Spark, Elasticsearch, vector databases).
- Solid foundations in algorithms, data structures, optimization, and statistical learning.
- Familiarity with MLOps tooling (MLflow, Airflow, SageMaker) and best-in-class CI/CD pipelines.
- Experience leading cross-functional teams or initiatives that brought research prototypes to production at scale.
- Domain expertise in reinforcement learning-from-human-feedback (RLHF), prompt engineering, or vector search.
Responsibilities
- Translate recent advances in LLMs, RAG pipelines, and agentic frameworks into production-ready solutions that solve real business problems.
- Design, prototype, and validate AI/ML models; run controlled experiments; and iterate quickly toward deployable systems.
- Own the product lifecycle for AI initiatives: define requirements, scope MVPs, set timelines, and align deliverables with strategic objectives.
- Guide and mentor junior data scientists and engineers in experimental design, model selection, and rigorous evaluation.
- Collaborate with data engineering to build and maintain robust real-time and batch data pipelines that power AI workloads.
- Establish best practices for model evaluation, testing, monitoring, and MLOps (CI/CD, automated retraining, observability).
- Conduct structured literature reviews and competitive analyses to keep the team current on emerging techniques and tools.
Other
- Bachelor’s degree in Computer Science or a related field is required
- Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field is preferred
- 5+ years of post-graduate, industry or applied-research experience developing and deploying AI/ML solutions.
- Exceptional written and verbal communication skills, with the ability to influence stakeholders across disciplines.
- Communicate technical concepts and research findings to both technical and non-technical audiences, converting insights into actionable product roadmaps.
