9 Embedding Techniques Jobs

Proven implementation experience in Data Science, Machine Learning, Deep Learning, and NLP for multiple domains. Strong programming skills in Python, with experience in libraries such as Transformers (Hugging Face), PyTorch, or TensorFlow. 6+ years of experience in data science, with at least 2 years focused on LLMs or Generative AI. Hands-on experience with fine-tuning, prompt engineering, RAG (Retrieval-Augmented Generation), and LLM evaluation. Familiarity with vector databases and embedding techniques. Experience deploying models using APIs, Docker, and cloud platforms Strong analytical, problem-solving, and communication skills. Experience in ML Ops, Model deployment, Model lifecycle and management Show more Show less

You are a senior professional with at least 6+ years of hands-on experience in Python focusing on AI technologies. Your proficiency lies in Python and you have worked with libraries such as NumPy, Pandas, scikit-learn, TensorFlow, or PyTorch. Your expertise includes a solid understanding of machine learning algorithms, model evaluation, and data preprocessing techniques. You have experience dealing with both structured and unstructured data sets. Additionally, you are familiar with version control systems like Git and collaborative development practices. Your strong problem-solving skills enable you to work effectively both independently and as part of a team. Desired Skills: - You have experience in natural language processing (NLP), computer vision, or time-series forecasting. - You are familiar with MLOps tools and practices for model deployment and monitoring. - Your background includes working with Generative AI models such as GPT, LLaMA, or Stable Diffusion. - You have knowledge of prompt engineering, fine-tuning, or embedding techniques for large language models (LLMs). - Hands-on experience with LLM frameworks like LangChain, Haystack, or Transformers (Hugging Face) is a plus. - You understand vector databases (e.g., Postgres, Pinecone) for retrieval-augmented generation (RAG) pipelines. - Any contributions to open-source AI/ML projects or published research would be beneficial. Locations: Hyderabad / Chennai / Bangalore / Pune. If you meet the above criteria and are interested in this opportunity, please share your resume at hr@neev.global or call 9429691736. This is a full-time position that requires you to work in person.,

As a Senior Data Science Engineer Lead at our Bangalore location, you will be responsible for spearheading the development of intelligent, autonomous AI systems. Your role will involve leveraging technologies such as agentic AI, LLMs, SLMs, Vector DB, and knowledge graphs to design and deploy innovative AI solutions, focusing on enhancing enterprise applications. You will work as part of a cross-functional agile delivery team, bringing an innovative approach to software development and contributing to all stages of software delivery. In this position, you will design and develop agentic AI applications using frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. You will also implement RAG Pipelines by integrating LLMs with vector databases and knowledge graphs to create dynamic retrieval systems. Additionally, you will fine-tune language models, train NER models, develop knowledge graphs, collaborate cross-functionally, and optimize AI workflows using MLOps practices. To be successful in this role, you should have 15+ years of professional experience in AI/ML development, proficiency in Python, Python API frameworks, SQL, and AI/ML frameworks like TensorFlow or PyTorch. Experience with deploying AI models on cloud platforms, familiarity with semantic technologies, MLOps tools, vector databases, RAG architectures, and hybrid search methodologies is essential. Strong problem-solving abilities, analytical thinking, excellent communication skills, and the ability to work independently on multiple projects are also key requirements. We offer a range of benefits including best in class leave policy, parental leaves, reimbursement under childcare assistance benefit, sponsorship for certifications, employee assistance program, hospitalization insurance, accident and term life insurance, health screening, training, coaching, and a culture of continuous learning to support your career progression. Join us at our Bangalore location to be part of a collaborative team that strives for excellence every day. Visit our company website for more information about Deutsche Bank Group and our inclusive work environment. We welcome applications from all individuals who share our values of responsibility, initiative, and collaboration.,

We are looking for a Generative AI Engineer to join our team specializing in AI applications involving Large Language Models (LLMs), Vision-Language Models (VLMs, and Computer Vision (CV). As a Generative AI Engineer, your primary responsibilities will include fine-tuning and optimizing LLMs for various tasks like summarization, classification, Q&A, and creative generation. You will also have the opportunity to work with Vision-Language Models such as BLIP, MiniGPT, and Kosmos for tasks like image captioning, visual question answering, and retrieval. Additionally, you will contribute to training and evaluating Computer Vision models for tasks like image generation, detection, or editing. Moreover, you will be expected to implement and test various prompt engineering and LoRA-based fine-tuning approaches for different tasks. Your role will involve preprocessing and managing multi-modal datasets containing images and text, and creating training/evaluation pipelines. It is essential to write clean, modular, and well-documented code for training, inference, and deployment purposes. Collaboration with backend, product, and design teams to integrate models into real-world applications will also be a key aspect of your job. Keeping yourself updated with the latest papers and open-source projects in the Generative AI space is crucial for this role. To be considered for this position, you should hold a Bachelor's degree in Computer Science, Artificial Intelligence, or a related field. A minimum of 3 years of experience in machine learning or deep learning, particularly in NLP or computer vision domains, is required. Proficiency in Python, PyTorch, and libraries such as Transformers (Hugging Face), OpenCV, or TorchVision is essential. Hands-on experience with LLMs like GPT, BERT, LLaMA, or CV models such as CLIP and Stable Diffusion is preferred. Familiarity with transformers, attention mechanisms, tokenization, and embedding techniques is also expected. Being comfortable with datasets, training loops, and evaluation metrics will be beneficial for this role.,

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