Interlinked is seeking a high-ownership AI/ML Engineer who can work independently and contribute to real production systems. The role involves building and iterating on ML models, implementing LLM pipelines, and experimenting with various machine learning approaches.
Responsibilities:
- Build and iterate on ML models using real datasets
- Implement LangChain-based LLM pipelines (RAG, tools, agents, evaluations)
- Train and evaluate models on tabular / structured data
- Assist in experimenting with RL / decision optimization approaches
- Read papers, blog posts, and documentation to solve problems independently
- Deploy models as APIs or services (basic MLOps exposure)
- Debug model behavior, improve performance, and document findings
- Contribute code that is production-ready, not just experimental
Requirements:
- Strong Python fundamentals
- Solid understanding of machine learning basics (training, validation, overfitting, metrics)
- Hands-on experience with at least one ML framework (PyTorch preferred)
- Prior exposure to LangChain or LLM orchestration frameworks
- Comfortable working with tabular data (pandas, feature engineering)
- Ability to work independently and learn without constant supervision
- Can clearly explain why they made a technical decision
- Built at least one end-to-end ML project (data → model → inference)
- Experience deploying models (FastAPI, Docker, cloud, or similar)
- Familiarity with reinforcement learning, bandits, or optimization loops
- Experience with LLMs beyond prompt usage (agents, tools, RAG, evaluation)
- Reads ML papers, blogs, or implements ideas from research