6 Embedding Techniques Jobs

You are invited to join our team as a Senior Python Developer specialized in AI/ML with a minimum of 6 years of relevant experience in Python and AI technologies. As a part of our dynamic team, you will be responsible for developing, deploying, and scaling AI/ML models using modern tools and frameworks. Your role will require proficiency in Python and experience with essential Python libraries such as NumPy, Pandas, and scikit-learn, along with TensorFlow or PyTorch. You should possess a solid understanding of machine learning algorithms, model evaluation techniques, and data preprocessing for both structured and unstructured data. Familiarity with version control systems like Git, strong problem-solving skills, and the ability to work both independently and collaboratively are key attributes we are looking for. Desirable skills for this role include experience in Natural Language Processing (NLP), Computer Vision, and Time-series forecasting. Exposure to MLOps tools for model deployment and monitoring, familiarity with Generative AI models like GPT and LLaMA, and hands-on experience with Prompt engineering, fine-tuning, and embedding techniques for LLMs are highly valued. Additionally, understanding LLM frameworks such as LangChain, Haystack, and Transformers (Hugging Face), as well as vector databases like Postgres and Pinecone, especially in RAG (Retrieval-Augmented Generation) pipelines, will be beneficial for this role. We also appreciate contributions to open-source AI/ML projects or published research papers. If you have the required skills and experience, along with a passion for AI/ML technologies, we would like to hear from you.,

We are seeking a highly motivated and experienced Technical Lead having experience to join our growing team. In this role, you will be responsible for leading complex data science projects, mentoring junior data scientists, and driving the development of innovative solutions that leverage data to achieve business objectives. You will apply your deep expertise in machine learning, statistical modeling, and data analysis to extract actionable insights and drive strategic decision-making. Experience: 1017 Years Job Type: Full-time Responsibilities: End-to-end delivery ownership of ML and GenAI use cases. Architect RAG pipelines and build enterprise-scale GenAI accelerators. Collaborate with architects and presales teams. Ensure code modularity, testability, and governance. Work closely with product managers and business stakeholders to understand requirements and deliver actionable AI solutions. Provide guidance and mentorship to junior team members. Manage project timelines, resources, and risk assessments. Collaborate with Data Engineers, AI/ML Engineers, Full Stack Engineers, and QA Engineers to ensure smooth integration of AI solutions. Stay updated with advancements in AI/ML technologies and best practices Required Skills: Strong background in AI/ML model development and deployment Proficient in Python, R, and other AI-related programming languages. Experience managing cross-functional teams in an Agile environment. Strong understanding of data science, cloud computing, and AI/ML frameworks (e.g., TensorFlow, PyTorch, etc.). LangChain, LangGraph, embedding techniques, prompt engineering. Classical ML: XGBoost, Random Forest, time-series forecasting. Show more Show less

We are seeking a dedicated Data Scientist with a strong background in Natural Language Processing (NLP) and expertise in Large Language Models (LLMs). As a part of our team, you will play a crucial role in the development, optimization, and implementation of open-source and API-based LLMs to address real-world challenges. Your primary responsibilities will revolve around constructing resilient GenAI pipelines, innovative internal tools, and customer-centric applications. This position offers you a remarkable chance to be at the forefront of Artificial Intelligence advancements and make significant contributions to the evolution of intelligent systems through the utilization of Retrieval-Augmented Generation (RAG) frameworks, vector databases, and real-time inference APIs. Your responsibilities will include fine-tuning and enhancing open-source LLMs tailored to specific business sectors, building and managing RAG pipelines utilizing tools like LangChain, FAISS, and ChromaDB, creating LLM-powered APIs for applications like chatbots, Q&A systems, summarization, and classification, as well as designing effective prompt templates and implementing chaining strategies to augment LLM performance across diverse contexts. To excel in this role, you must possess a deep understanding of NLP principles and advanced deep learning techniques for text data, hands-on experience with LLM frameworks like Hugging Face Transformers or OpenAI APIs, familiarity with tools such as LangChain, FAISS, and ChromaDB, proficiency in developing REST APIs for machine learning models, proficiency in Python along with expertise in libraries such as PyTorch or TensorFlow, and a solid grasp of data structures, embedding techniques, and vector search systems. Desirable qualifications include prior experience in LLM fine-tuning and evaluation, exposure to cloud-based ML deployment on platforms like AWS, GCP, or Azure, and a background in information retrieval, question answering, or semantic search. If you are passionate about generative AI and eager to work with cutting-edge NLP and LLM technologies, we are excited to connect with you.,

You are a Data Science Engineer who will be contributing to the development of intelligent, autonomous AI systems. The ideal candidate should have a strong background in agentic AI, LLMs, SLMs, vector DB, and knowledge graphs. Your responsibilities will include deploying AI solutions that leverage technologies such as Retrieval-Augmented Generation (RAG), multi-agent frameworks, and hybrid search techniques to enhance enterprise applications. As part of the flexible scheme, you will enjoy various benefits such as a best-in-class leave policy, gender-neutral parental leaves, childcare assistance benefit reimbursement, sponsorship for industry-relevant certifications, employee assistance program, comprehensive hospitalization insurance, accident and term life insurance, and health screening. Your key responsibilities will involve designing and developing Agentic AI Applications using frameworks like LangChain, CrewAI, and AutoGen, implementing RAG Pipelines, fine-tuning Language Models, training NER Models, developing Knowledge Graphs, collaborating cross-functionally, and optimizing AI workflows. To excel in this role, you should have at least 4 years of professional experience in AI/ML development, proficiency in Python, Python API frameworks, SQL, and familiarity with AI/ML frameworks like TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms, understanding of LLMs, SLMs, semantic technologies, and MLOps tools is required. Additionally, hands-on experience with vector databases, embedding techniques, and developing AI solutions for specific industries will be beneficial. You will receive support through training, coaching, and a culture of continuous learning to aid in your career progression. The company strives for a culture of empowerment, responsibility, commercial thinking, initiative, and collaboration. They promote a positive, fair, and inclusive work environment for all individuals. For further information about the company and its teams, please visit the company website at https://www.db.com/company/company.htm. Join a team that celebrates success and fosters a culture of excellence and inclusivity.,

As a Data Scientist specializing in Natural Language Processing (NLP) and Large Language Models (LLMs), you will play a crucial role in designing, fine-tuning, and deploying cutting-edge open-source and API-based LLMs to address real-world challenges. Your primary focus will be on creating robust GenAI pipelines, innovative internal tools, and engaging client-facing applications. You will have the exciting opportunity to work at the forefront of AI technology, contributing to the advancement of intelligent systems through the utilization of Retrieval-Augmented Generation (RAG) frameworks, vector databases, and real-time inference APIs. Your responsibilities will include fine-tuning and optimizing open-source LLMs for specific business domains, constructing and managing RAG pipelines using tools like LangChain, FAISS, and ChromaDB, as well as developing LLM-powered APIs for diverse applications such as chat, Q&A, summarization, and classification. Additionally, you will be tasked with designing effective prompt templates and implementing chaining strategies to enhance LLM performance across various contexts. To excel in this role, you should possess a strong foundation in NLP fundamentals and deep learning techniques for text data, hands-on experience with LLM frameworks like Hugging Face Transformers or OpenAI APIs, and familiarity with tools such as LangChain, FAISS, and ChromaDB. Proficiency in developing REST APIs to support ML models, expertise in Python programming with knowledge of libraries like PyTorch or TensorFlow, and a solid grasp of data structures, embedding techniques, and vector search systems are also essential. Preferred qualifications include prior experience in LLM fine-tuning and evaluation, exposure to cloud-based ML deployment (AWS, GCP, Azure), and a background in information retrieval, question answering, or semantic search. If you are passionate about generative AI and eager to contribute to the latest developments in NLP and LLMs, we are excited to connect with you.,

Data Modeling & Transformation, Visualization & Reporting, Data Sources & Integration,Sharing & Deployment