Company DescriptionMoleculyst Ventures Private Limited is an AI research and engineering startup focused on hallucination detection, verifiable reasoning, and autonomous research agents. We are developing systems that help language models ground their claims in evidence, use external tools, verify reasoning, and carry out research over extended periods. Our work combines deep learning, mechanistic interpretability, information retrieval, and formal verification. Our goal is to build reliable AI workers that can investigate problems, run experiments, evaluate results, and improve through structured feedback. Our current focus includes hallucination detection and explainability, alongside the infrastructure needed for autonomous experimentation. Role Description – Deep Learning Specialist (LLM Research & Reliability)This is a remote contract role for a Deep Learning Specialist with hands-on experience in language models and a strong mathematical foundation. You will design and evaluate methods for understanding model behavior, detecting unsupported claims, and improving the reliability of AI agents. The role involves working with model internals, building reproducible experiments, and translating research ideas into working prototypes. We are looking for someone who can explain their modeling choices, question assumptions, and distinguish promising experimental results from reliable evidence.

Key Responsibilities
• Design and implement methods for hallucination detection, uncertainty estimation, and evidence-grounded generation
• Investigate model internals, including hidden representations, attention mechanisms, and activation patterns
• Research and reproduce relevant work in mechanistic interpretability, representation learning, and LLM reliability




• Develop training and fine-tuning experiments for specific reasoning and verification tasks
• Integrate models with retrieval systems, tools, and verification components
• Contribute to autonomous research workflows that formulate hypotheses, run experiments, and evaluate outcomes
• Conduct rigorous evaluation using appropriate baselines, ablation studies, error analysis, and held-out datasets
• Build reproducible training and evaluation pipelines, with explicit experiment logs and technical documentation Required QualificationsDeep Learning & Mathematics
• Strong understanding of linear algebra, probability, statistics, and optimization
• Solid grasp of backpropagation, loss functions, regularization, and generalization
• Practical understanding of transformers, attention, tokenization, embeddings, and autoregressive generation
• Ability to read research papers, understand their mathematical formulations, and implement their core methods
• Ability to design experiments that test a specific hypothesis and identify confounding factors or data leakage Programming & Frameworks
• Strong proficiency in Python and PyTorch
• Hands-on experience running, inspecting, or fine-tuning language models
• Familiarity with Hugging Face Transformers or comparable model tooling
• Experience with GPU-based experimentation, debugging, and memory management
• Familiarity with version control,



experiment tracking, and reproducible workflows Research & Evaluation
• Evidence of substantive work through research projects, repositories, publications, or well-documented experiments
• Ability to select meaningful metrics and interpret results critically
• Ability to explain model behavior and experimental findings clearly, including limitations and failed approaches Preferred / Advantageous Qualifications
• Experience with hallucination detection, uncertainty estimation, calibration, or out-of-distribution detection
• Experience with mechanistic interpretability, activation probing, steering, or causal interventions
• Familiarity with retrieval, reranking, and grounding over documents or structured databases
• Exposure to formal logic, typed representations, Z3, or Lean
• Experience building agents with tool use, memory, and iterative experimentation
• Familiarity with information geometry, optimal transport, or related mathematical approaches to representation analysis
• Experience optimizing inference or training open-weight models under compute constraints A relevant degree is welcome, but demonstrated ability and quality of work matter more than formal credentials. What We Value Most
• Mathematical clarity and careful reasoning
• Working implementations supported by reproducible evidence
• Curiosity and the willingness to challenge an appealing hypothesis
• Clear communication about uncertainty and limitations
• Ownership of a research problem from initial formulation through implementation and evaluation
• You should be able to explain what your model does, why you chose the method, how you tested it, and where it fails.

📌 Deep Learning Specialist (India)
🏢 Moleculyst
📍 India