25 T5 Jobs

As an AI/ML Developer, you will be responsible for utilizing programming languages such as Python for AI/ML development. Your proficiency in libraries like NumPy, Pandas for data manipulation, Matplotlib, Seaborn, Plotly for data visualization, and Scikit-learn for classical ML algorithms will be crucial. Familiarity with R, Java, or C++ is a plus, especially for performance-critical applications. Your role will involve building models using Machine Learning & Deep Learning Frameworks such as TensorFlow and Keras for deep learning, PyTorch for research-grade and production-ready models, and XGBoost, LightGBM, or CatBoost for gradient boosting. Understanding model training, validation, hyperparameter tuning, and evaluation metrics like ROC-AUC, F1-score, precision/recall will be essential. In the field of Natural Language Processing (NLP), you will work with text preprocessing techniques like tokenization, stemming, lemmatization, vectorization techniques such as TF-IDF, Word2Vec, GloVe, and Transformer-based models like BERT, GPT, T5 using Hugging Face Transformers. Experience with text classification, named entity recognition (NER), question answering, or chatbot development will be required. For Computer Vision (CV), your experience with image classification, object detection, segmentation, and libraries like OpenCV, Pillow, and Albumentations will be utilized. Proficiency in pretrained models (e.g., ResNet, YOLO, EfficientNet) and transfer learning is expected. You will also handle Data Engineering & Pipelines by building and managing data ingestion and preprocessing pipelines using tools like Apache Airflow, Luigi, Pandas, Dask. Experience with structured (CSV, SQL) and unstructured (text, images, audio) data will be beneficial. Furthermore, your role will involve Model Deployment & MLOps where you will deploy models as REST APIs using Flask, FastAPI, or Django, batch jobs, or real-time inference services. Familiarity with Docker for containerization, Kubernetes for orchestration, and MLflow, Kubeflow, or SageMaker for model tracking and lifecycle management will be necessary. In addition, your hands-on experience with at least one cloud provider such as AWS (S3, EC2, SageMaker, Lambda), Google Cloud (Vertex AI, BigQuery, Cloud Functions), or Azure (Machine Learning Studio, Blob Storage) will be required. Understanding cloud storage, compute services, and cost optimization is essential. Your proficiency in SQL for querying relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and familiarity with big data tools like Apache Spark, Hadoop, or Databricks will be valuable. Experience with Git and platforms like GitHub, GitLab, or Bitbucket will be essential for Version Control & Collaboration. Familiarity with Agile/Scrum methodologies and tools like JIRA, Trello, or Asana will also be beneficial. Moreover, you will be responsible for writing unit tests and integration tests for ML code and using tools like pytest, unittest, and debuggers to ensure the quality of the code. This position is Full-time and Permanent with benefits including Provident Fund and Work from home option. The work location is in person.,

You are a Machine Learning & Generative AI Engineer responsible for designing, building, and deploying advanced ML and GenAI solutions. This role presents an exciting opportunity to work on cutting-edge AI systems, such as LLM fine-tuning, Transformer architectures, and RAG pipelines, while also contributing to traditional ML model development for decision-making and automation. With a minimum of 3 years of experience in Machine Learning, Deep Learning, and AI model development, you are expected to demonstrate a strong proficiency in Python, PyTorch, TensorFlow, Scikit-Learn, and MLflow. Your expertise should encompass Transformer architectures (such as BERT, GPT, T5, LLaMA, Falcon) and attention mechanisms. Additionally, experience with Generative AI, including LLM fine-tuning, instruction tuning, and prompt optimization is crucial. You should be familiar with RAG (Retrieval-Augmented Generation) embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows. A solid foundation in statistics, probability, and optimization techniques is essential for this role. You should have experience working with cloud ML platforms like Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, or GCP Vertex AI. Familiarity with Big Data & Data Engineering tools like Spark, Hadoop, Databricks, and SQL/NoSQL databases is required. Proficiency in CI/CD, MLOps, and automation pipelines (such as Airflow, Kubeflow, MLflow) is expected, along with hands-on experience with Docker and Kubernetes for scalable ML/LLM deployment. It would be advantageous if you have experience in NLP & Computer Vision areas, including Transformers, BERT/GPT models, YOLO, and OpenCV. Exposure to vector search & embeddings for enterprise-scale GenAI solutions, multimodal AI, Edge AI / federated learning, RLHF (Reinforcement Learning with Human Feedback) for LLMs, real-time ML applications, and low-latency model serving is considered a plus. Your responsibilities will include designing, building, and deploying end-to-end ML pipelines covering data preprocessing, feature engineering, model training, and deployment. You will develop and optimize LLM-based solutions for enterprise use cases, leveraging Transformer architectures. Implementing RAG pipelines using embeddings and vector databases to integrate domain-specific knowledge into LLMs will also be part of your role. Fine-tuning LLMs on custom datasets for domain-specific tasks and ensuring scalable deployment of ML & LLM models on cloud environments are critical responsibilities. Collaborating with cross-functional teams comprising data scientists, domain experts, and software engineers to deliver AI-driven business impact is expected from you.,

Job Description: Graduate degree in a quantitative field (CS, statistics, applied mathematics, machine learning, or related discipline) Good programming skills in Python with strong working knowledge of Pythons numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, etc. Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. Predictive modelling experience in Python (Time Series/ Multivariable/ Causal) Experience applying various machine learning techniques and understanding the key parameters that affect their performance Experience of building systems that capture and utilize large data sets to quantify performance via metrics or KPIs Excellent verbal and written communication Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects. Roles & Responsibilities: Lead a team of Data Engineers, Analysts and Data scientists to carry out following activities: Connect with internal / external POC to understand the business requirements Coordinate with right POC to gather all relevant data artifacts, anecdotes, and hypothesis Create project plan and sprints for milestones / deliverables Spin VM, create and optimize clusters for Data Science workflows Create data pipelines to ingest data effectively Assure the quality of data with proactive checks and resolve the gaps Carry out EDA, Feature Engineering & Define performance metrics prior to run relevant ML/DL algorithms Research whether similar solutions have been already developed before building ML models Create optimized data models to query relevant data efficiently Run relevant ML / DL algorithms for business goal seek Optimize and validate these ML / DL models to scale Create light applications, simulators, and scenario builders to help business consume the end outputs Create test cases and test the codes pre-production for possible bugs and resolve these bugs proactively Integrate and operationalize the models in client ecosystem Document project artifacts and log failures and exceptions. Measure, articulate impact of DS projects on business metrics and finetune the workflow based on feedbacks Show more Show less

Job Title: Generative AI Engineer Location: Hyderabad, India Department: Artificial Intelligence / Machine Learning Job Type: Full-time | On-site Experience Level: Mid-Senior / Senior (48 years preferred) About the Role: We are looking for a talented and passionate Generative AI Engineer to join our AI/ML team in Hyderabad . You will work on cutting-edge projects involving large language models (LLMs), diffusion models, and transformer architectures to build scalable and innovative generative solutions. Key Responsibilities: Design, develop, and deploy generative AI models for various business use cases. Fine-tune large language models (like GPT, LLaMA, Mistral, etc.) on domain-specific datasets. Work with multimodal models (text, image, video, audio) and generative techniques (e.g., GANs, VAEs, diffusion models). Collaborate with cross-functional teams to understand product requirements and implement AI-driven features. Optimize models for performance, accuracy, and latency on production-scale systems. Stay updated with the latest research in generative AI and bring best practices into the team. Required Skills & Qualifications: Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or related field. 3+ years of experience in building and deploying AI/ML models, preferably generative models. Proficient in Python and ML frameworks like PyTorch or TensorFlow. Solid understanding of transformer-based architectures (BERT, GPT, T5, etc.). Experience with Hugging Face Transformers, LangChain, or similar libraries. Exposure to prompt engineering, RAG (Retrieval-Augmented Generation), and LLMOps. Familiarity with MLOps tools (e.g., MLflow, Weights & Biases, Kubernetes). Strong problem-solving and communication skills. Preferred (Good to Have): Experience with multimodal models or image generation (e.g., DALL•E, Stable Diffusion). Knowledge of cloud platforms (AWS, Azure, GCP) and GPU/TPU deployment. Publications or contributions in AI research communities (arXiv, GitHub, etc.). Why Join Us? Work on impactful AI projects in a fast-paced and collaborative environment. Competitive salary with performance bonuses. Flexible work hours and hybrid setup. Access to state-of-the-art computing resources and open-source models. If you are passionate about building the next generation of AI systems and want to work with a team that values innovation and excellence, we’d love to hear from you! Please share your updated profiles to naseeruddin.khaja@infosharesystems.com

Greetings ! At present we have an urgent leadership opening with an esteemed client. Position : AI Architect - AVP / SAVP Job Location : Noida / Gurgaon / Pune / Bangalore ( Hybrid Model ) Mandatory Skills Required - AI Architect, Data Science, GenAI, Vertex AI, Python, NLP, Deep Learning Frameworks Designation- AI Architect Role- Permanent/ Full time Experience- 11-16 years Location- Noida/ Gurgaon/ Pune/ Bangalore Shift- 12:00 PM to 10PM (10 Hours Shift. Also depends on the project/work dependencies) Working Days- 5 days Work Mode- Hybrid Mandatory Skills- Transformer Models - either finetune or training on Open-Source Transformer based models. Build and fine-tune large-scale language models using PyTorch and modern libraries. Should have done projects on LLM, NLP, LLAMA, Hugging face, RAG, Gen AI. Hands-on on Python coding experience. Machine Learning or Deep Learning. Good experience into Agentic AI and should have done end -to-end projects in Gen AI. Skills: 1. Proven experience as an NLP and ML Engineer or similar role 2. Have worked on open-source LLM (like Falcon and llama) for various text generation task 3. Have done SFT or PEFT on decoder based LLM for a specific text generation task 4. Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling 5. Have worked on BERT models for intent classifiers and entity extraction techniques 6. Ability to write robust and testable code 7. Experience with machine learning frameworks (PyTorch) 8. Knowledge of Python, Groovy Script, BPMN 9. An analytical mind with problem-solving abilities 10. Degree in Computer Science, Mathematics, Computational Linguistics or similar field Responsibilities: 1. Study and transform data science prototypes 2. Design NLP applications 3. Use effective text representations to transform natural language into useful features 4. Find and implement the right algorithms and tools for NLP tasks 5. Develop NLP systems according to requirements 6. Train the developed model and run evaluation experiments 7. Perform statistical analysis of results and refine models 8. Extend ML libraries and frameworks to apply in NLP tasks 9. Remain updated in the rapidly changing field of machine learning Plz reply to the following queries along with your updated resume : Current Organization : Current Designation : Reason for change : Reporting to : Date of Birth : Qualification : PAN Number : Current CTC (Fixed + Variable) : CTC Expectation : Any other offer in hand or in process : If yes, Please mention the offer details : Official Notice Period : Are you serving the Notice period : Mention your Last Working Date : Present Team size : Maximum Team Size handled : Location Staying at : Location Interested in (Noida / Gurgaon / Pune / Bangalore) : Technical Skills Expertise : Domains worked on : Total years of experience : Yrs of exp as AI Architect : Yrs of exp in Data Scientist role : Yrs of exp in Artificial Intelligence : Yrs of exp in GenAI : No. of end -to-end projects done in Gen AI : Yrs of exp in Transformer based models : Yrs of exp in Open-Source Transformer based models : Mention the Transformer based models worked on (like BERT, T5, RoBerta) : Yrs of exp in Large Language Models (LLMs) : Yrs of exp in NLP : Yrs of exp into Hugging face : Yrs of exp in Retrieval-Augmented Generation (RAG) : Yrs of exp in Deep Learning Framework : Mention the deep learning frameworks you have worked on : Yrs of exp in Machine learning : Yrs of exp in open-source LLM (like Falcon and llama) : Mention the Open-source transformer models worked on : Yrs of exp in Pytorch : Yrs of exp in Tensorflow, Keras : Yrs of exp in Python : How much would you rate yourselves in Python on a scale of 1-10 (10 being the highest) : Yrs of exp in cloud platforms (AWS, Azure, GCP) : Ever interviewed by EXL SERVICE in past : About client : Client has been 25+ years in existence with 29000+ employees globally and deals in: Digital Intelligence: Outcomes: Real digital transformation creates deeper customer experiences, faster speed to market, growing revenues and profitability. Everything we do is outcome oriented, ensuring the business is not only transformed, its built to stay ahead. Context: Were experts in more than technology and advanced analytics; we’re experts in our clients’ industries and businesses. This enables us to look deeper to identify and capitalize on opportunities to outperform. Orchestration: Our digital specialists understand both technology and the context in which it is applied. This enables to orchestrate complex and interdependent technologies – AI, robotics, analytics, machine learning and more – to deliver targeted solutions. Operations: BFSI (Banking, Financial service & Insurance) IT (Product Based Organization) & Consulting, BPO Analytics: Acquired Inductis. 2000+ employees in analytics division. Ranked 2nd best Analytics organization across the world. 22 Offices in India : 6 in Noida, 3 in Gurgaon / Pune / Chennai / Kochi each and 1 in Jaipur / Bangalore / Hyderabad / Ahmedabad. Thanks and Regards, Rashmi K. Vishwakarma M : 9833965671 / 9321442718 rashmi@ultimatesearch.in Ultimate Search Pvt. Ltd. Life is too short for a wrong job

About the Role We are seeking a highly skilled Senior NLP Engineer with expertise in large language models (LLMs), prompt engineering, and transformer-based architectures. The ideal candidate will have strong experience fine-tuning, deploying, and optimizing advanced NLP models for real-world applications such as summarization, text generation, and question answering. You will collaborate with cross-functional teams to design scalable, production-ready solutions while addressing challenges such as bias, hallucinations, and knowledge cutoffs. Key Responsibilities: Fine-tune pre-trained models on domain-specific datasets to optimize for summarization, text generation, question answering, and related tasks. Prompt Engineering: Design, test, and iterate on contextually relevant prompts to guide model outputs for desired performance. Implement and refine instruction-based prompting strategies to achieve contextually accurate results. Apply zero-shot, few-shot, and many-shot learning methods to maximize model performance without extensive retraining. Leverage Chain-of-Thought (CoT) prompting for structured, step-by-step reasoning in complex tasks. Evaluate model performance using BLEU, ROUGE, and other relevant metrics; identify opportunities for improvement. Deploy trained and fine-tuned models into production environments, integrating with real-time systems and pipelines. Identify, monitor, and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs. Work closely with cross-functional teams (data scientists, engineers, product managers) to design scalable and efficient NLP-driven solutions. Must-Have Skills: 7+ years of overall experience in software/AI development with at least 2+ years in transformer-based NLP models. 4+ years of hands-on expertise with transformer architectures (GPT, BERT, T5, RoBERTa, etc.). Strong understanding of attention mechanisms, self-attention layers, tokenization, embeddings, and context windows. Proven experience in fine-tuning pre-trained models for NLP tasks (summarization, classification, text generation, translation, Q&A). Expertise in prompt engineering, including zero-shot, few-shot, many-shot learning, and prompt template creation. Experience with instruction-based prompting and Chain-of-Thought prompting for reasoning tasks. Proficiency in Python and NLP libraries/frameworks such as Hugging Face Transformers, SpaCy, NLTK, PyTorch, TensorFlow. Strong knowledge of model evaluation metrics (BLEU, ROUGE, perplexity, etc.). Experience in deploying models into production environments. Awareness of bias, hallucinations, and limitations in LLM outputs. Good to Have: Experience with LLM observability tools and monitoring pipelines. Exposure to cloud platforms (AWS, GCP, Azure) for scalable model deployment. Knowledge of MLOps practices for model lifecycle management. Location-Remote,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad, Mumbai, Hyderabad

NLP & LLM Specialis (Immediate Joiners only)- transformer-based models (GPT, BERT, T5, RoBERTa) and NLP tasks(focus on text gen, summarization, ques ans, classification) Python NLP Libraries (Hugging Face, SpaCy, NLTK) CoT Prompt engg Prompt Template Required Candidate profile fine-tuning pre-trained models Model Expertise Prompt Engineering Instruction-Based Prompting Zero-shot, Few-shot, Many-shot Learning Model Deployment CoT Model Evaluation Bias Awareness Collaboration

JD: 7+ yrs exp with 2+ yrs in NLP using transformer models (GPT, BERT, T5, RoBERTa). Skilled in text generation, summarization, Q&A, and classification. Strong expertise in model fine-tuning, deployment, and optimization.

You are an experienced Data Scientist with 2-4 years of hands-on experience in developing machine learning and deep learning models, specifically in the domain of text analytics and natural language processing (NLP). You will be responsible for taking ownership of the entire process, from understanding requirements to proposing and designing effective solutions. This role requires a professional capable of developing innovative projects in NLP, text analytics, and text generation. Your key responsibilities will include collaborating with stakeholders to gather and understand business requirements, proposing and designing innovative solutions using machine learning and deep learning techniques, developing and validating models for text analytics, NLP, and text generation applications, analyzing and assessing the effectiveness of solutions through testing and validation, conducting comprehensive data analysis and statistical modeling to extract insights and drive data-driven decision-making, communicating insights and results clearly to both technical and non-technical audiences, staying updated on industry trends and advancements in data science and NLP, and mentoring and guiding juniors to foster a culture of continuous learning and improvement. Required Skill Set: - Good analytical skills and an inherent ability to solve problems. - Bachelors or masters degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. - Proven expertise in text analytics, NLP, machine learning, and deep learning. - Strong proficiency in Python, demonstrating algorithmic thinking. - Proven experience with machine learning libraries such as NLTK, spaCy, Scikit-learn, Pandas, and NumPy. - Experience in training and validating models using deep learning frameworks like TensorFlow or PyTorch, including Hugging Face. - Experience in tuning and validating models from the families of BERT, T5, BART, or FLAN-T5. - Experience in performing hyperparameter tuning in at least one project. Good To Have Skill Set: - In-depth knowledge of the fundamentals of transformer-based models and related techniques. - Hands-on experience with generative models (e.g., GANs, VAEs, GPT). - Experience developing with frameworks like LangChain and LlamaIndex. - Other GenAI related skills include RAG pipeline design, Multi-agentic solution.,

As a Gen AI Consultant with 3-4 years of experience in Generative AI, NLP, and Machine Learning, you will be an essential part of our team based in Hyderabad. Your primary role will involve developing AI-driven solutions, refining models, and integrating AI technologies into various business applications. Your key responsibilities will include designing and implementing Generative AI models such as LLMs, NLP, and Deep Learning. You will be required to fine-tune and optimize these AI models for improved performance and scalability. Additionally, you will play a crucial role in deploying chatbots, automation tools, and other AI-based applications using Python, TensorFlow, PyTorch, and Hugging Face frameworks. Furthermore, you will be responsible for deploying AI models through APIs, cloud platforms like AWS, Azure, Google AI, and vector databases. It will be essential for you to stay updated on the latest advancements in the field of AI and provide recommendations for innovative solutions. To excel in this role, you should possess 3-4 years of practical experience in Generative AI, NLP, and ML. Proficiency in LLMs such as GPT, BERT, T5, and experience in AI model deployment are essential. Strong knowledge of prompt engineering, data preprocessing, and model optimization is required. Experience with cloud-based AI services and MLOps, along with excellent problem-solving and communication skills, will be beneficial for your success in this position.,

Reimagine Travel with AI At our organization, we are actively involved in shaping the future of travel by utilizing AI-driven innovation. We are leveraging LLMs and AI agents to provide personalized and seamless travel experiences for our customers. By joining our team, you will have the opportunity to contribute towards enhancing Myra, our conversational AI chatbot, and play a pivotal role in redefining how travelers plan their journeys. The ideal candidate for the Senior Data Scientist position should possess 4-6 years of relevant experience. In this role, you will be responsible for developing and fine-tuning LLMs and AI agents tailored for trip planning and dynamic personalization. Additionally, you will work on building generative AI models to enhance intelligent travel assistants, virtual experiences, and pricing engines. You will be tasked with optimizing real-time decision-making processes by leveraging advanced NLP techniques and high-quality data. Collaboration with cross-functional teams to deploy scalable AI solutions for millions of travelers will also be a key aspect of this role. We are seeking individuals with a strong background in PyTorch, TensorFlow, and transformer models such as GPT-3/4, BERT, T5. Proficiency in NLP, LLM fine-tuning, and data-centric ML is highly desirable. A proven track record in areas like search relevance, personalization engines, and scalable AI pipelines will be advantageous. The ability to approach problem-solving proactively and thrive in fast-paced environments is crucial for success in this role. By joining our team, you will become part of a dynamic group that is revolutionizing the travel industry through the application of cutting-edge AI and Generative AI technologies. Your work will have a direct impact on millions of users worldwide, offering you a unique opportunity to make a difference in the field of travel technology. Candidates applying for this position are required to have an educational background in BE/BTech from Tier 1 institutes (IITs/IIITs/NITs). A preferred qualification would be an MS or Ph.D. in CS/ECE/AI/ML or equivalent fields, demonstrating a strong academic foundation in relevant areas.,

You are a highly experienced Lead Machine Learning Engineer specializing in Speech AI, Natural Language Processing (NLP), and Generative AI (GenAI). Your role is crucial in designing and expanding a production-grade speech-based virtual assistant powered by Large Language Models (LLMs), advanced audio signal processing, and multimodal intelligence. Collaborating closely with product, research, and DevOps teams, you will lead a group of ML engineers to create and implement cutting-edge AI solutions. In this role, your responsibilities include architecting and implementing advanced machine learning models for speech recognition (ASR), text-to-speech (TTS), NLP, and multimodal tasks. You will lead the development and fine-tuning of Transformer-based LLMs, including encoder-decoder architectures for audio and text tasks. Additionally, you will build custom audio-LLM interaction frameworks incorporating modality fusion, speech understanding, and language generation techniques. Your duties also involve designing and deploying LLM-powered virtual assistants with real-time speech interfaces for dialog, voice commands, and assistive technologies. You will integrate speech models with backend NLP pipelines to handle complex user intents, contextual understanding, and response generation effectively. Furthermore, you will design and implement end-to-end ML pipelines covering data ingestion, preprocessing, feature extraction, model training, evaluation, and deployment. Developing reproducible and scalable training pipelines using MLOps tools such as MLflow, Kubeflow, and Airflow with robust monitoring and model versioning will be part of your responsibilities. You will also drive CI/CD for ML workflows, model containerization (Docker), and orchestration using Kubernetes/serverless infrastructure. To stay updated with the latest advancements in Speech AI, LLMs, and GenAI, you will evaluate and drive the adoption of novel techniques. Experimenting with self-supervised learning, prompt tuning, parameter-efficient fine-tuning (PEFT), and zero-shot/multilingual speech models will be essential for innovation and progress. The required technical skills for this role include: - 10+ years of hands-on experience in machine learning, with a deep focus on audio (speech) and NLP applications. - Expertise in Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems, including tools like Wav2Vec, Whisper, Tacotron, FastSpeech, etc. - Strong knowledge of Transformer architectures like BERT, GPT, T5, and encoder-decoder LLM variants, including training/fine-tuning at scale. - Proficiency in Python programming and deep learning frameworks like PyTorch and TensorFlow. - In-depth understanding of audio signal processing concepts such as MFCCs, spectrograms, wavelets, sampling, filtering, etc. - Experience with multimodal machine learning, including the fusion of speech, text, and contextual signals. - Deployment of ML services with Docker, Kubernetes, and experience with distributed training setups on GPU clusters or cloud platforms (AWS, GCP, Azure). - Proven experience in building production-grade MLOps frameworks and maintaining model lifecycle management. - Experience with real-time inference, latency optimization, and efficient decoding techniques for audio/NLP systems. Preferred qualifications for this role include: - Master's or Ph.D. in Computer Science, Machine Learning, Signal Processing, or related technical discipline. - Publications or open-source contributions in speech, NLP, or GenAI. - Familiarity with LLM alignment techniques, RLHF, prompt engineering, and fine-tuning using LoRA, QLoRA, or adapters. - Previous experience in deploying voice-based conversational AI products at scale.,

You are a talented and innovative AI/ML Engineer with a strong background in machine learning and deep learning. You have a keen interest in Generative AI (GenAI) and are excited to explore, implement, and scale GenAI models. Your primary responsibilities include designing and deploying end-to-end AI/ML solutions, experimenting with cutting-edge GenAI frameworks and tools, and collaborating with cross-functional teams to solve business problems using ML solutions. Your key responsibilities involve designing and developing robust ML models, including traditional and deep learning approaches. You will also build, train, fine-tune, and deploy Generative AI models for various use cases such as text, image, or code generation. Utilizing AWS services like SageMaker, Lambda, EC2, S3, and Glue to build scalable AI/ML solutions is an essential part of your role. Additionally, you will create and automate ML pipelines using CI/CD and MLOps best practices, conduct data preprocessing, feature engineering, and EDA for model development, and ensure model performance, fairness, and explainability throughout the lifecycle. To excel in this role, you should hold a Bachelor's/Masters degree in Computer Science, AI/ML, Data Science, or a related field and have at least 3 years of hands-on experience in machine learning and deep learning using Python with TensorFlow, PyTorch, Hugging Face, etc. Strong hands-on experience with AWS AI/ML services, experience in deploying LLMs or transformer-based models in production, and familiarity with GenAI tools like Hugging Face Transformers, LangChain, OpenAI API, Bedrock, or LLamaIndex are required. You should also possess working knowledge of REST APIs, microservices, and containerized deployments, proficiency in MLOps tools such as MLflow, SageMaker Pipelines, or Kubeflow, and strong communication skills to present complex ML concepts clearly. Preferred qualifications include experience with prompt engineering, fine-tuning, or RAG techniques, AWS Machine Learning Specialty certification or equivalent, exposure to NLP, computer vision, or multi-modal GenAI models, and contributions to open-source GenAI projects or research. Stay updated with the latest trends in GenAI and propose innovative solutions using LLMs or transformer-based architectures to drive continuous improvement in AI/ML solutions.,

Senior Software Engineer - AI Backend As Relyance AIs Senior Software Engineer, AI Backend , you will strategize, drive, and execute on the core initiatives connecting output of NLP (Natural Language Processing) and AI models with the Relyance product. You will partner with cross-functional stakeholders to design and build a flexible, powerful, and robust NLP backend that scales the impact of AI for our customers. Given that you are constructing the foundation for a system with complex data that rapidly evolves over time, you need to pay close attention to detail, anticipate and welcome constant change, maintain a forward-thinking outlook, all while being fast and scrappy enough to address present needs. As a Senior Software Engineer - AI Backend, your role will include: Strategy: using your experience and understanding of how complex backends and data evolve over time, you will create and execute a roadmap for a system that enables high velocity AI development while creating stability on the product side Execution: make customer-centric prioritization decisions to balance between immediate impact and long-term bets and partner with the team manager to drive alignment and collaboration with other engineering teams Design: deeply understand how everything fits together; architect systems to balance scrappiness for the current needs with a forward-thinking outlook to improve and scale our infrastructure; continuously look for opportunities to automate and build tools to lower operational barriers Hands-on: being a key member of the team solving its most complex problems with the simple, pragmatic solutions Learning: in this role, you will have ample opportunities to become a hands-on AI/ML engineer by learning practical use of AI technologies such as LLMs (Large Language Models, e.g. ChatGPT and GPT-4), smaller models like BERT and T5, frameworks like PyTorch and TensorFlow, model training and data curation workflows, etc. This role could be a fit for you if you bring: 7+ years of experience with a track record of being a key member of teams building complex backends, especially backends that deal with complex data Expert level proficiency in Python Strong data structures, algorithms, and OO software design and implementation skills Ability to learn and operate across full stack, from ML and NLP, to cloud infrastructure, to UI frontend Experience as a creative and strategic thinker with mindset to build powerful, robust, and flexible systems A get stuff done attitude and enjoy being hands-on and working alongside the team to solve its most pressing problems in a fast-paced, collaborative environment A track record of successfully influencing product direction through a strong perspective that motivates engineers to develop simple, pragmatic solutions to complex problems Skills in communicating with clear and concise, active listening and empathy skills, and a respectful, collaborative approach that earns the trust of your peers Bonus points for: Experience with ML and NLP in particular Experience with a privacy technology Startup Experience An advanced technical degree Show more Show less

As an AIML - LLM Gen AI Engineer, your primary responsibility will be to design, develop, and implement solutions using transformer-based models for various Natural Language Processing (NLP) tasks. This includes tasks such as text generation, summarization, question answering, classification, and translation. You will be working extensively with transformer models like GPT, BERT, T5, RoBERTa, and similar architectures. Your deep understanding of model architectures, attention mechanisms, and self-attention layers will be crucial in effectively utilizing Large Language Models (LLMs) to generate human-like text. You will lead efforts in fine-tuning pre-trained LLMs and other transformer models on domain-specific datasets to optimize performance for specialized NLP tasks. In your role, you will apply your knowledge of attention mechanisms, context windows, tokenization, and embedding layers in model development and optimization. It will be essential to address and mitigate issues related to biases, hallucinations, and knowledge cutoffs that can impact LLM performance and output quality. You will craft clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs, including the use of instruction-based prompting. Additionally, you will implement and experiment with zero-shot, few-shot, and many-shot learning techniques to maximize model performance without extensive retraining. Your iterative approach to prompt engineering strategies will involve refining outputs, rigorously testing model performance, and ensuring consistent and high-quality results. You will also be responsible for creating prompt templates for repetitive tasks that are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting will enable you to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Your contribution will span the entire lifecycle of machine learning models in an NLP context, including training, fine-tuning, and deployment. **Required Skills & Qualifications:** - A minimum of 8 years of experience working with transformer-based models and NLP tasks, focusing on text generation, summarization, question answering, classification, and similar applications. - Proficiency in transformer models such as GPT, BERT, T5, RoBERTa, and foundational models. - Strong familiarity with model architectures, attention mechanisms, and self-attention layers for generating human-like text. - Proven experience in fine-tuning pre-trained models on domain-specific datasets for various NLP tasks. - Knowledge of attention mechanisms, context windows, tokenization, and embedding layers. - Awareness of biases, hallucinations, and knowledge cutoffs affecting LLM performance. - Ability to craft clear, concise, and contextually relevant prompts for LLMs. - Experience in zero-shot, few-shot, and many-shot learning techniques. - Proficiency in Python and NLP libraries like Hugging Face Transformers, SpaCy, NLTK. - Solid experience in training, fine-tuning, and deploying ML models in an NLP context. - Strong problem-solving skills and analytical mindset. - Excellent communication and collaboration abilities for remote or hybrid work environments. - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or related quantitative field. This role requires a combination of technical expertise in AI/ML, NLP, and transformer models, along with strong problem-solving and communication skills to achieve effective results in the field.,

You are a highly skilled AI/ML/Gen AI Data Scientist with expertise in Generative AI, Machine Learning, Deep Learning, and Natural Language Processing (NLP). You have a strong foundation in Python-based AI frameworks and experience in developing, deploying, and optimizing AI models for real-world applications. Your responsibilities include developing and implementing AI/ML models, working with Deep Learning architectures like Transformers (BERT, GPT, LLaMA) and CNNs/RNNs, fine-tuning and optimizing Large Language Models (LLMs) for various applications, designing and training custom Machine Learning models using structured and unstructured data, leveraging NLP techniques such as text summarization and Named Entity Recognition (NER), implementing ML pipelines, and deploying models in cloud environments (AWS/GCP/Azure). You will collaborate with cross-functional teams to integrate AI-driven solutions into business applications and stay updated with the latest AI advancements to apply innovative techniques to improve model performance. To qualify for this role, you should have 1 to 3 years of experience in AI/ML, Deep Learning, and Generative AI, strong proficiency in Python and ML frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn, hands-on experience with NLP models including BERT, GPT, T5, LLaMA, and Stable Diffusion, expertise in data preprocessing, feature engineering, and model evaluation, experience with MLOps, cloud-based AI deployment, and containerization (Docker, Kubernetes), knowledge of vector databases and retrieval-augmented generation (RAG) techniques, ability to fine-tune LLMs and work with prompt engineering, strong problem-solving skills, and the ability to work in agile environments. You should hold a Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, or Information Technology. Preferred skills include experience with Reinforcement Learning (RLHF) and multi-modal AI, familiarity with AutoML, Responsible AI (RAI), and AI Ethics, exposure to Graph Neural Networks (GNNs) and time-series forecasting, contributions to open-source AI projects or research papers. Your skills should encompass Machine Learning (ML), Generative AI, Artificial Intelligence (AI), Python, and Large Language Models (LLM).,

As an AI/ML & GenAI Developer Intern at ArgyleEnigma Tech Labs working on the FinDocGPT project, you will be part of a groundbreaking initiative to make complex financial documents easily understandable for millions of Indians. This internship opportunity offers a stipend ranging from 8,000 to 12,000 INR per month for a duration of 6 months, starting immediately. At FinDocGPT, we are dedicated to leveraging cutting-edge AI/ML and GenAI technologies to provide a transformative solution that bridges the financial literacy gap in India. Our product, FinDocGPT, is India's first AI-powered assistant that decodes intricate financial documents into simple, regional language, covering areas such as health insurance, loans, and mutual fund terms and conditions. Supported by Google for Startups and the Reserve Bank Innovation Hub, we are on a mission to empower individuals by offering financial information in a language they understand. As an AI/ML & Generative AI Developer Intern, you will have the opportunity to gain hands-on experience in deploying GenAI models, NLP pipelines, and ML-based document processing. Your responsibilities will include working on document classification, NER, and summarization using advanced LLMs such as LLaMA, Mistral, Groq, and open-source models. Additionally, you will preprocess, clean, and structure financial documents in various formats like PDFs, scans, and emails. Collaborating with the product and design teams, you will contribute to building smart and user-friendly interfaces. To excel in this role, you should possess a strong understanding of Python, NLP, and basic ML concepts. Familiarity with transformers like BERT, T5, or GPT architectures is essential. Experience, even in an academic setting, with HuggingFace, LangChain, or LLM APIs is preferred. Knowledge of Google Cloud, AWS, or Docker would be a bonus. We are looking for individuals who are eager to learn, experiment quickly, and create a tangible impact. By joining us, you will receive direct mentorship from industry experts with backgrounds in companies such as Morgan Stanley, PIMCO, and Google. You will gain real-world exposure to AI applications tailored for the Indian market and have the opportunity to transition into a full-time role based on your performance. Your work will directly contribute to enhancing financial inclusion in India. To apply for this internship, please send your CV, GitHub/portfolio, and a brief statement explaining why you are interested in this role to info@argyleenigma.com or apply via https://tinyurl.com/hr-aetl with the subject line "Internship Application - FinDocGPT." This internship is based in Gandhinagar, Gujarat, and requires in-person work. The expected start date is 01/08/2025.,

Role & responsibilities Design, prototype, and deploy AI-driven applications leveraging LLMs (GPT-4, Perplexity, Claude, Gemini, etc.) and open-source transformer models. Lead or co-lead end-to-end AI/GenAI solutions : from data ingestion, entity extraction, and semantic search to user-facing interfaces. Implement RAG (Retrieval-Augmented Generation) architectures, knowledge grounding pipelines, and prompt orchestration logic. Fine-tune transformer models (BERT, RoBERTa, T5, LLaMA) on custom datasets for use cases like: Document understanding Conversational AI Question answering Summarization & Topic Modeling Integrate LLM workflows into scalable backend architectures with APIs and frontends. Work closely with business teams and pharma SMEs to translate requirements into GenAI solutions . Mentor junior engineers and contribute to AI capability development across the organization. Tech Stack & Skills Required Programming & Libraries : Python, FastAPI, LangChain, Pandas, PyTorch/TensorFlow, Transformers (HuggingFace), OpenAI SDK. Data Extraction & Processing : PDFMiner, PyMuPDF, Tabula, PyPDF2, Tesseract OCR, python-pptx. Gen AI / LLMs : OpenAI (GPT), Gemini, Perplexity, Cohere, DeepSeek, Mistral, LLaMA, BERT, RoBERTa, T5, Falcon. Use Cases : NER, Summarization, QA, Document Parsing, Clustering, Topic Modeling, QA over docs. Embedding & Vector Databases : Pinecone, FAISS, ChromaDB. RAG & Retrieval Pipelines : LangChain, Haystack, custom retrievers. Frontend/Backend Integration : React (preferred), FastAPI/Flask, REST/GraphQL APIs. Versioning & Deployment : Git, Docker, CI/CD (basic), cloud knowledge is a plus (AWS/GCP/Azure). Preferred candidate profile Degree in Computer Science, Engineering, Data Science, or related field (BE/BTech/MTech/MCA). 35 years of hands-on experience in AI/ML/NLP/LLM solution development. Strong understanding of GenAI, Prompt Engineering, LLM internals , and multi-layered data architectures. Exposure to pharma/healthcare domain is a significant plus. Excellent problem-solving skills, self-learner, and ability to work in cross-functonal teams. Experience developing new applications within an agile environment preferred. Ability to work independently and as part of a team. Exposure to MLOPs will be an added advantage.

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. EY-Consulting AI Enabled Automation Developer Staff -Python We are looking to hire people with strong AI Enabled Automation skills and who are interested in learning new technologies in the process automation space Azure . GenAI , large Lang Models(LLM). RAG ,Vector DB , Graph DB ,Python At EY, youll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Responsibilities Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals, demonstrating the potential of AI enabled automation applications. Ensure seamless integration of optimized solutions into the overall product or system Collaborate with cross-functional teams to understand requirements, to integrate solutions into cloud environments (Azure, GCP, AWS, etc.) and ensure it aligns with business goals and user needs Educate team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project Requirements 2 to 3 years of relevant professional experience Expertise in Python programming including experience with Al/machine learning frameworks like TensorFlow, PyTorch, Keras, Langchain, MLflow, Promtflow(Good to have) 1-2 years of working knowledge of NLP and LLMs like BERT, GPT-3/4, T5, etc. Knowledge of how these models work and how to fine-tune them Expertise in prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Knowledge of retrieval augmented generation (RAG) Knowledge of Knowledge Graph RAG Strong analytical and problem-solving skills with the ability to think critically and troubleshoot issues Excellent communication skills, both verbal and written in English What we look for A Team of people with commercial acumen, technical experience and enthusiasm to learn new things in this fast-moving environment An opportunity to be a part of market-leading, multi-disciplinary team of 1400 + professionals, in the only integrated global transaction business worldwide. Opportunities to work with EY Advisory practices globally with leading businesses across a range of industries What working at EY offers At EY, were dedicated to helping our clients, from startups to Fortune 500 companies and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way thats right for you EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

Research & Development - AI Prompt Engineer Company Overview : We are Motive - the worlds leading provider of device management for mobile, fixed and IOT as well as managing the omni-channel customer experience which through its business logic drives actions, runs proactive care campaigns and improves customer satisfaction. Deployed by leading service providers worldwide, Motives device management and service management platform drive revenue, reduce customer care costs and automate each customer interaction. A relaunched brand with a long history and pedigree, at Motive we differentiate ourselves by creating innovative technical solutions, packaging them in ways that simplify operational complexity and time to market, and we never forget that we only succeed when our customers succeed. As a member of the Motive team, you will share a passion for being part of an exciting team of talented individuals, with a focus on building sustained long-term growth, and a fantastic place to work. Surrounded by individuals of exceptional ability and commitment, you will have the opportunity both to contribute to our continued business success, and to also invest in your own personal development. At Motive we hire only passionate team orientated people to join our business. Are you one of them? Position Summary: As a Research and Development AI Prompt Engineer, you will be at the forefront of creating and enhancing our software products. You will maximize the value of the R&D team’s delivery in research, design, prototyping, and development of new features and solutions. In this role, you will focus on developing, optimizing, and fine-tuning AI prompts for various natural language processing (NLP) and generative AI systems. You will work closely with software engineers to improve model outputs, refine AI understanding, and ensure the quality and accuracy of generated content. As an AI Prompt Engineer, you’ll play a key role in creating effective and efficient prompts that maximize the performance of AI models, particularly those focused on tasks such as anomaly detection, prediction, question answering, summarization, and more. Main Responsibility Areas: Prompt Design and Optimization Develop, test, and optimize natural language prompts for a variety of tasks, ensuring that AI models produce accurate, contextually relevant, and high-quality responses Experiment with different prompt engineering techniques, strategies, and styles to improve AI model outputs in various scenarios (e.g., anomaly detection, chatbot interactions, code generation, etc.) Analyze and refine existing prompts to ensure the desired AI model behavior AI Model Fine-tuning Collaborate with R&D and Professional Services software engineers to fine-tune pre-trained models using custom prompts for specific business requirements or user needs. Conduct prompt-based testing and validation to assess model performance and quality. Develop feedback loops to iteratively improve prompt designs based on model output quality. Performance Optimization: Analyze AI model outputs and fine tune prompts to improve accuracy and performance. Work closely with R&D software engineers to integrate prompt-engineered models into production systems and applications. Partner with product managers and UX/UI designers to understand user needs and ensure that AI-generated content aligns with user expectations and business goals. Document prompt engineering strategies, guidelines, and best practices. Maintain detailed records of model performance metrics and improvements over time. Provide regular updates to stakeholders on prompt optimization results and model performance. Stay up-to-date with the latest trends and techniques in AI, NLP, and prompt engineering. Create prototypes and proof-of-concept models to demonstrate the feasibility and potential of new ideas. Key Skills & Competencies: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Linguistics, AI, Data Science, or a related field. Advanced degrees and relevant certifications are a plus. Strong understanding of natural language processing (NLP) techniques and machine learning models (e.g., GPT, BERT, T5). Experience with AI prompt engineering, fine-tuning, and content generation tasks. Familiarity with large-scale pre-trained models, including transformers and generative models. Proficiency in programming languages such as Python, with a focus on libraries like Hugging Face, TensorFlow, PyTorch, or OpenAI’s API. Troubleshooting skills. Familiarity with AI platforms and cloud computing services (e.g., AWS, GCP, Azure). Expertise in Atlassian Jira and Confluence tools as well as Microsoft SharePoint Excellent verbal and written communication skills. Ability to articulate technical concepts to both technical and non-technical stakeholders. Ability to work effectively in a collaborative team environment. Strong interpersonal skills and a proactive attitude. Ability to quickly learn and apply new technologies. Flexibility to adapt to changing priorities and project requirements. Work Experience Requirements: Experience working with generative models such as GPT-3/4, BERT, or T5. Familiarity with conversational AI, chatbots, and interactive AI systems. Experience with data labeling, model evaluation, and data annotation. A strong portfolio showcasing previous work in prompt design or AI-driven NLP systems. Knowledge of AI ethics, bias mitigation, and content moderation techniques. Limitations and Disclaimer The above job description is meant to describe the general nature and level of work being performed; it should not be construed as an exhaustive list of all responsibilities, duties and skills required for the position. All job requirements are subject to possible modification to reasonably accommodate individuals with disabilities. Some requirements may exclude individuals who pose a direct threat or significant risk to the health and safety of themselves or other employees. This job description in no way states or implies that these are the only duties to be performed by the employee occupying this position. Employees will be required to follow any other job-related instructions and to perform other job-related duties requested by their manager.

Roles and Responsibilities: Model Expertise : Work with transformer models such as GPT , BERT , T5 , RoBERTa , and others for a variety of NLP tasks, including text generation, summarization, classification, and translation. Model Fine-Tuning : Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering. Prompt Engineering : Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. Iterate on prompts to optimize model performance. Instruction-Based Prompting : Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives. Zero-shot, Few-shot, Many-shot Learning : Utilize zero-shot , few-shot , and many-shot learning techniques to improve model performance without the need for full retraining. Chain-of-Thought (CoT) Prompting : Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations. Model Evaluation : Use evaluation metrics such as BLEU , ROUGE , and other relevant metrics to assess and improve the performance of models for various NLP tasks. Model Deployment : Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications. Bias Awareness : Be aware of and mitigate issues related to bias , hallucinations , and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs. Collaboration : Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions. Must Have Skill Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks , with a focus on text generation , summarization , question answering , classification , and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer) , BERT (Bidirectional Encoder Representations from Transformers) , T5 (Text-to-Text Transfer Transformer) , RoBERTa , and similar models. Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation , summarization , question answering , classification , and translation . Familiarity with concepts like attention mechanisms , context windows , tokenization , and embedding layers . Awareness of biases , hallucinations , and knowledge cutoffs that can affect LLM performance and output quality. Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. Experience in instruction-based prompting Use of zero-shot , few-shot , and many-shot learning techniques for maximizing model performance without retraining. Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. Experience in training, fine-tuning, and deploying machine learning models in an NLP context. Understanding of model evaluation metrics (e.g., BLEU, ROUGE) Qualification: BE/B.Tech or Equivalent degree in Computer Science or related field. Excellent communication skills in English, both verbal and written

We are looking for Indias top 1% NLP Engineers for a unique job opportunity to work with the industry leaders Who can be a part of the community? We are looking for top-tier Natural Language Processing Engineers with experience in text analytics, LLMs, and speech processing If you have experience in this field then this is your chance to collaborate with industry leaders Whats in it for you? Pay above market standards The role is going to be contract based with project timelines from 2 12 months, or freelancing Be a part of Elite Community of professionals who can solve complex AI challenges Work location could be: Remote (Highly likely) Onsite on client location Deccan AIs Office: Hyderabad or Bangalore Responsibilities: Develop and optimize NLP models (NER, summarization, sentiment analysis) using transformer architectures (BERT, GPT, T5, LLaMA) Build scalable NLP pipelines for real-time and batch processing of large text data and optimize models for performance and deploy on cloud platforms (AWS, GCP, Azure) Implement CI/CD pipelines for automated training, deployment, and monitoring & integrate NLP models with search engines, recommendation systems, and RAG techniques Ensure ethical AI practices and mentor junior engineers Required Skills: Expert Python skills with NLP libraries (Hugging Face, SpaCy, NLTK) Experience with transformer-based models (BERT, GPT, T5) and deploying at scale (Flask, Kubernetes, cloud services) Strong knowledge of model optimization, data pipelines (Spark, Dask), and vector databases Familiar with MLOps, CI/CD (MLflow, DVC), cloud platforms, and data privacy regulations Nice to Have: Experience with multimodal AI, conversational AI (Rasa, OpenAI API), graph-based NLP, knowledge graphs, and A/B testing for model improvement Contributions to open-source NLP projects or a strong publication record What are the next steps? Register on our Soul AI website Our team will review your profile Clear all the screening rounds: Clear the assessments once you are shortlisted Profile matching and Project Allocation: Be patient while we align your skills and preferences with the available project Skip the Noise Focus on Opportunities Built for You! Location : - Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune,India

Role & responsibilities Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks, with a focus on text generation, summarization, question answering, classification, and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), T5 (Text-to-Text Transfer Transformer), RoBERTa, and similar models. Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation, summarization, question answering, classification, and translation. Familiarity with concepts like attention mechanisms, context windows, tokenization, and embedding layers. Awareness of biases, hallucinations, and knowledge cutoffs that can affect LLM performance and output quality. Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. Experience in instruction-based prompting Use of zero-shot, few-shot, and many-shot learning techniques for maximizing model performance without retraining. Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g., Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g., GPT, BERT, T5) for text generation tasks. Experience in training, fine-tuning, and deploying machine learning models in an NLP context. Understanding of model evaluation metrics (e.g., BLEU, ROUGE)

Summary:- We are looking for a seasoned and proactive Manager with 7-10 years of experience in Canadian accounting and taxation , preferably in an outsourcing (BPO/KPO) setup. The ideal candidate will possess a strong foundation in Canadian GAAP, CRA regulations, and end-to-end compliance processes including T1, T2, T4, GST/HST filings. This individual should have a proven track record of leading teams (10+ members) and managing direct client relationships with Canadian businesses or CPAs . Strong leadership, excellent communication, and hands-on experience with accounting and tax software like QuickBooks, CaseWare, TaxCycle, and Xero are essential for this role. Role Summary: This is a client-facing leadership role responsible for managing a team of Canadian tax and accounting professionals. The Manager will lead end-to-end service delivery , ensure regulatory compliance , and be accountable for client satisfaction, performance reviews , and team development . The role requires strong technical expertise, people management, and communication skills. Key Responsibilities: Client Relationship Management: Act as the main point of contact for Canadian clients including CPAs and businesses across provinces. Lead client calls, understand client expectations, and manage the delivery of all accounting and taxation services. Proactively handle client queries, escalations, and service issues. Participate in onboarding and transition of new clients. Team Leadership & People Management: Lead, mentor, and manage a team of 10+ accounting and tax professionals . Assign workloads, monitor productivity, and ensure deliverables are met with quality and timeliness. Conduct training sessions , knowledge-sharing meetings, and performance reviews . Identify team development needs and plan upskilling strategies. Accounting & Tax Compliance: Supervise and review preparation of: Financial Statements and Working Papers T1 (Personal Tax Returns) T2 (Corporate Tax Returns) T4, T5, GST/HST filings Ensure month-end/year-end closing processes are completed, including bank and ledger reconciliations. Keep up-to-date with changes in CRA regulations , Canadian tax laws, and compliance requirements. Oversee documentation, workpapers, and ensure compliance with internal control standards . Process Management & Quality Control: Identify and implement process improvement and automation opportunities . Develop SOPs and standardized work templates across client engagements. Ensure adherence to SLA/KPI metrics , conduct internal audits and peer reviews. Liaise with internal quality and transition teams for service excellence. Technical Proficiency: Canadian GAAP and CRA guidelines. Accounting & tax software expertise in: QuickBooks Desktop/Online CaseWare TaxCycle Xero ProFile Excel (Advanced) Soft Skills: Strong leadership and decision-making abilities. Excellent English communication skills, both verbal and written. Ability to work independently and manage multiple clients and projects simultaneously. Analytical mindset with attention to detail and documentation. What We Offer: A leadership position with high visibility in a growing Canadian division. Exposure to global clients and diverse accounting/taxation scenarios. Dynamic and collaborative work environment. Structured career growth path with international exposure and upskilling opportunities. Attractive salary package with performance-linked incentives.