About the job

About the Role

We’re looking for an AI/ML Engineer with a deep interest in autonomous agents, adaptive matching systems, and data transformation pipelines. This role focuses on building intelligent systems that learn over time, interact with dynamic data, and produce outcomes that reduce human decision-making overhead in complex domains.

You’ll work at the intersection of intelligent automation, workflow design, and human-centered AI, creating systems that adapt, scale, and continuously improve.

Key Focus Areas

• Autonomous Agents & LLM Workflows

• Develop AI agents that can independently interpret goals, fetch or transform data, and initiate downstream actions.
• Implement multi-step workflows using LLMs and agentic frameworks (e.g., LangChain, ReAct, or custom orchestration).
• Enable agent behaviors such as querying APIs, formatting outputs, scheduling tasks, or generating reports.

2. Adaptive Matching & Personalization Systems

• Design and train models that match entities (e.g., users, institutions, products) based on mutual preferences and learned behavior.
• Build feedback loops into matching logic to improve accuracy and relevance over time.
• Apply clustering, similarity scoring, ranking algorithms, and reinforcement learning as needed.

3. Data Extraction & Transformation Intelligence

• Use AI to extract structured insights from semi-structured and unstructured data (e.g., PDFs, scans, tables).
• Normalize and transform input data into standard formats that can feed into evaluation or comparison systems.
• Apply grading logic, weighting schemes, or rule-based models to derive scores, rankings, or classifications.

You Might Be a Fit If You Have:

• 3+ years of experience in AI/ML engineering or applied data science.
• Strong Python skills and experience with modern ML/AI stacks (e.g., transformers, OpenAI API, LangChain, pandas, PyTorch/TensorFlow).
• Exposure to agentic AI design, autonomous workflows, or orchestration platforms.
• A product-minded approach: you think about accuracy, latency, usability, and iteration.
• Comfort building end-to-end prototypes that evolve into production-ready systems.

Nice to Have

• Experience with knowledge retrieval, embeddings, and RAG pipelines.
• Familiarity with OCR and NLP for tabular data and document understanding.
• Background in data-driven personalization, matchmaking, or recommendation engines.
• Experience translating messy real-world inputs into structured, evaluable outputs.

Why This Matters

The next wave of AI goes beyond single queries; it’s about systems that observe, adapt, and act. If you’re excited about applying AI in ways that reduce manual work, enhance decision-making, and produce tangible outputs in real-world workflows, this role is for you.