Tror - AI for everyone
Job Title: Data Scientist (In-Person Interview)
Location: Remote
Duration: Long-Term
Visa: Any visa is Fine (Need 4+ years of experience in Data Scientist)
Interview process: 1st round virtual and 2nd round (F2F mandatory)
End Client: Working in Implementation Project
Note: Need at least 4+ years of experience complete into Data Scientist.
Note: while sharing the resume please share writeup for data scientist for your experience.
Please share resumes at Akhil@tror.ai
Key Responsibilities
Lead end-to-end training and fine-tuning of Large Language Models (LLMs), including both open-source (e.g., Qwen, Llama, Mistral) and closed-source (e.g., OpenAI, Gemini, Anthropic) ecosystems. Architect and implement Graph RAG pipelines, including knowledge graph representation and retrieval for enhanced contextual grounding. Design, train, and optimize semantic and dense vector embeddings for document understanding, search, and retrieval. Develop semantic retrieval systems with advanced document segmentation and indexing strategies. Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU and multi-node training. Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to align model behavior with human preferences and domain-specific goals. Collaborate with cross-functional teams to translate business needs into AI-driven solutions and deploy them in production environments. Designing and implementing analytical frameworks. Developing predictive and prescriptive models. Preferred Qualifications
PhD or master's degree in computer science, Machine Learning, or related field. 4+ years of experience in applied AI/ML, with a strong track record of delivering production-grade models. Deep Expertise In
LLM training and fine-tuning (e.g., GPT, Llama, Mistral, Qwen) Graph-based retrieval systems (Graph RAG, knowledge graphs) Embedding models (e.g., BGE, E5, SimCSE) Semantic search and vector databases (e.g., FAISS, Weaviate, Milvus) Document segmentation and preprocessing (OCR, layout parsing) Distributed training frameworks (NCCL, Horovod, DeepSpeed) High-performance networking (InfiniBand, RDMA) Model fusion and ensemble techniques (stacking, boosting, gating) Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms) Symbolic AI and rule-based systems Meta-learning and Mixture of Experts architectures Reinforcement learning (e.g., RLHF, PPO, DPO) Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics. Exercise independent judgment in methods, techniques, and evaluation criteria on data science projects, overseeing the end-to-end process from problem definition to model implementation. Proficiency with programming languages like Python, R, and SQL. Strong background in predictive modeling, classification, segmentation, and optimization. Extensively worked in any Cloud environment. Bonus Skills
Familiarity with regulatory and compliance frameworks in AI deployment. Contributions to open-source AI projects or published research. And/Or ability to take research papers to poc production. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
IT Services and IT Consulting Referrals increase your chances of interviewing at Tror - AI for everyone by 2x We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr
Lead end-to-end training and fine-tuning of Large Language Models (LLMs), including both open-source (e.g., Qwen, Llama, Mistral) and closed-source (e.g., OpenAI, Gemini, Anthropic) ecosystems. Architect and implement Graph RAG pipelines, including knowledge graph representation and retrieval for enhanced contextual grounding. Design, train, and optimize semantic and dense vector embeddings for document understanding, search, and retrieval. Develop semantic retrieval systems with advanced document segmentation and indexing strategies. Build and scale distributed training environments using NCCL and InfiniBand for multi-GPU and multi-node training. Apply reinforcement learning techniques (e.g., RLHF, RLAIF) to align model behavior with human preferences and domain-specific goals. Collaborate with cross-functional teams to translate business needs into AI-driven solutions and deploy them in production environments. Designing and implementing analytical frameworks. Developing predictive and prescriptive models. Preferred Qualifications
PhD or master's degree in computer science, Machine Learning, or related field. 4+ years of experience in applied AI/ML, with a strong track record of delivering production-grade models. Deep Expertise In
LLM training and fine-tuning (e.g., GPT, Llama, Mistral, Qwen) Graph-based retrieval systems (Graph RAG, knowledge graphs) Embedding models (e.g., BGE, E5, SimCSE) Semantic search and vector databases (e.g., FAISS, Weaviate, Milvus) Document segmentation and preprocessing (OCR, layout parsing) Distributed training frameworks (NCCL, Horovod, DeepSpeed) High-performance networking (InfiniBand, RDMA) Model fusion and ensemble techniques (stacking, boosting, gating) Optimization algorithms (Bayesian, Particle Swarm, Genetic Algorithms) Symbolic AI and rule-based systems Meta-learning and Mixture of Experts architectures Reinforcement learning (e.g., RLHF, PPO, DPO) Experience applying causal inference techniques (e.g., causal impact analysis, uplift modeling, DoWhy) to marketing and engagement analytics. Exercise independent judgment in methods, techniques, and evaluation criteria on data science projects, overseeing the end-to-end process from problem definition to model implementation. Proficiency with programming languages like Python, R, and SQL. Strong background in predictive modeling, classification, segmentation, and optimization. Extensively worked in any Cloud environment. Bonus Skills
Familiarity with regulatory and compliance frameworks in AI deployment. Contributions to open-source AI projects or published research. And/Or ability to take research papers to poc production. Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries
IT Services and IT Consulting Referrals increase your chances of interviewing at Tror - AI for everyone by 2x We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr