1380 Deep Learning Jobs - Page 43

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Job Summary: The ideal candidate will have a strong background in data analysis, machine learning, and statistical modeling, along with the ability to derive actionable insights from complex data sets. Responsibilities: Data Collection and Preprocessing: Acquire, clean, and preprocess data from various sources to ensure data quality and reliability. Work with big data technologies and tools for efficient data processing. Exploratory Data Analysis (EDA): Conduct exploratory data analysis to understand data patterns, trends, and anomalies. Identify relevant variables and features for further analysis. Statistical Modeling and Machine Learning: Develop and implement statistical models and machine learning algorithms to solve business problems. Perform predictive modeling, classification, clustering, and regression analysis as needed. Evaluate model performance and make improvements using techniques like cross-validation and hyperparameter tuning. Collaboration and Communication: Collaborate with cross-functional teams, including data engineers, business analysts, and software developers. Communicate technical concepts and results to non-technical stakeholders in a clear and understandable manner. Provide guidance and support to team members on data-related tasks and projects. Qualifications: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Proven experience in data analysis, machine learning, and statistical modeling. Proficiency in programming languages such as Python, R, or SQL. Familiarity with GenAI and implementing LLM Familiarity with machine learning libraries/frameworks (e.g., TensorFlow, scikit-learn, PyTorch). Experience with big data platforms (e.g., Hadoop, Spark) and cloud services (e.g., AWS, Azure) is a plus. Strong analytical and problem-solving skills with attention to detail. Excellent communication and collaboration abilities. Ability to work independently and manage multiple projects simultaneously. Note: Job Location: Chennai, Bangalore, Pune, Coimbatore, Mumbai Work Mode: Hybrid ( 3 Days WFO and 2 Days WFH) Work Time: 2pm to 11pm ( UK Shift time) Notice Preferred: 0-30 Days

Role & responsibilities Develop and maintain AI-based solutions using Python. Design, develop, and deploy AI-driven applications with a focus on GenAI Chatbots & AI Agents. Implement GenAI Chatbots, including ingestion and query pipelines, using at least one cloud platform ( Azure, or GCP). Implement Agentic AI framework-based solutions. Develop data ingestion pipelines for efficient data processing and transformation. Ensure high data integrity and performance in AI-driven workflows. Deploy AI models on cloud platforms such as Azure, or GCP. Implement best practices for scalability, security, and cost optimization in cloud-based AI solutions. Conduct regular performance tuning, debugging, and troubleshooting of AI models and applications. Implement monitoring and logging mechanisms for AI-driven systems. Work closely with cross-functional teams, including data scientists, ML engineers, and software developers, to integrate AI solutions. Document technical specifications, workflows, and best practices for AI development. Stay updated with the latest advancements in GenAI, Agentic AI technologies to bring innovation into the organization. Preferred candidate profile Extensive experience in AI software development with strong proficiency in Python. Hands-on experience with GenAI, Agentic AI. Experience in developing Generative AI chatbots, Agentic AI frameworks including ingestion pipelines, query pipelines, and Retrieval-Augmented Generation (RAG) using at least one cloud platform. Solid understanding of machine learning techniques and algorithms. Strong knowledge of data structures, algorithms, and software design principles. Healthcare domain experience is a plus.

We are seeking a skilled and experienced Machine Learning Engineer specialized in Natural Language Processing (NLP) and Computer Vision to join our team. The ideal candidate should have a strong foundation in ML and AI principles, coupled with a proven track record of developing and deploying a minimum of 20+ models in these domains. Role & responsibilities Develop and implement state-of-the-art machine learning algorithms and models for NLP and computer vision applications. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Conduct thorough data analysis, pre-processing, and feature engineering to extract meaningful insights from structured and unstructured data. Design and implement scalable and efficient machine learning pipelines for training, evaluation, and inference. Experiment with various deep learning architectures, hyperparameters, and optimization techniques to improve model performance. Stay updated with the latest advancements in ML and AI research and evaluate their potential applications in our domain. Work closely with software engineers to integrate ML models into production systems and ensure their robustness and scalability. Perform rigorous testing and validation of models to ensure their accuracy, reliability, and generalization capability. Continuously monitor and maintain deployed models, and implement necessary updates and enhancements as required. Document code, methodologies, and findings effectively, and contribute to internal knowledge sharing initiatives Preferred candidate profile Strong theoretical understanding of machine learning algorithms, deep learning frameworks, and statistical modeling techniques. Proficiency in programming languages such as Python, along with experience in popular ML libraries such as TensorFlow, PyTorch, or scikit-learn. Hands-on experience in developing and deploying machine learning models for NLP and computer vision tasks, with a demonstrable portfolio of projects. Solid understanding of natural language processing techniques, including text classification, sentiment analysis, named entity recognition, etc. Familiarity with computer vision concepts such as image classification, object detection, image segmentation, etc., and experience with frameworks like OpenCV or TensorFlow. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.

Must understand Gen AI models o Hands on with Python with basic ML libraries o Building NLP engine (pre-processing, modelling) o Understanding of Deep Learning frameworks for NLU, NLG & MLOps o Docker containerization, building CI/CD pipeline o Hands on with GCP Data Science tool for Building, Training, Deploying Models, especially Vertex Role & responsibilities Preferred candidate profile

Job Description: We are seeking a highly motivated and skilled AI Developer to join our dynamic team. The ideal candidate should have hands-on experience in designing, developing, and deploying AI and machine learning models to solve real-world problems. You will work closely with data scientists, software engineers, and product teams to build intelligent applications. Key Responsibilities: Design and develop AI/ML models based on business requirements Preprocess and analyze structured and unstructured data Implement Deep Learning and NLP algorithms using frameworks like TensorFlow, PyTorch, and Scikit-learn Collaborate with software engineers to integrate models into production environments Build and optimize pipelines for data ingestion, model training, and inference Monitor model performance and retrain as needed Research and implement state-of-the-art algorithms Create dashboards or front-end demos using Streamlit or similar tools (optional) Key Skills Required: Programming: Python (Must), R (Optional), Java (Good to have) AI/ML: TensorFlow, PyTorch, Keras, Scikit-learn Data Science: Pandas, NumPy, Matplotlib, Seaborn NLP: Hugging Face Transformers, NLTK, SpaCy Computer Vision: OpenCV, YOLO, CNNs Model Deployment: Flask, FastAPI, Docker, AWS/Azure/GCP Databases: SQL, MongoDB, Firebase (optional) Version Control: Git, GitHub Preferred Qualifications: Bachelors or Master’s degree in Computer Science, AI, Data Science, or related field Strong mathematical foundation in statistics, linear algebra, and probability Excellent problem-solving skills and attention to detail Strong communication and teamwork skills Why Join Us? Work on cutting-edge AI solutions Collaborative and inclusive work environment Opportunity to grow in a fast-paced tech-driven organization Exposure to real-world enterprise and consumer AI applications

Key Responsibilities: Design, develop, and optimize NLP models for text classification, sentiment analysis, chatbots, and language generation. Work with deep learning models such as Transformers (BERT, GPT, LSTMs) to enhance NLP capabilities. Implement and fine-tune machine learning algorithms for text analytics and information extraction. Collaborate with data engineers and software developers to integrate NLP solutions into real-world applications.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

Key Responsibilities: Provide strategic guidance on AI adoption, ethics, and governance within the organization. Advise on AI-driven business models, innovation strategies, and regulatory compliance. Evaluate AI research, development, and deployment strategies to ensure ethical and sustainable growth. Mentor and collaborate with internal teams on best practices in AI, data science, and machine learning. Assess AI risks, biases, and challenges, providing solutions for responsible AI implementation.

We are seeking a motivated Junior Software Developer to join our dynamic team focused on developing the low-level software platform for next-generation in-vehicle embedded devices. The ideal candidate will have a strong passion for embedded systems, C++ development, and a keen interest in the practical deployment of AI models on specialized hardware. You will work closely with senior developers, AI/ML engineers and data scientists to design, implement, and optimize robust and efficient low-level software solutions that unlock the full potential of our in-vehicle AI capabilities. Key Responsibilities: Develop, implement, and maintain the low-level software platform modules for in-vehicle embedded devices, specifically targeting NPU and other accelerator integration. Design and implement software for efficient deployment, loading, and execution of AI/ML models (including GenAI) on embedded hardware accelerators. Optimize models for real-time performance, memory footprint, and power consumption on constrained embedded systems. Collaborate with cross-functional teams to gather requirements and translate them into technical specifications. Write clean, efficient, and well-documented code following best practices. Participate in code reviews and contribute to team knowledge sharing. Debug and troubleshoot issues in existing applications. Stay updated with the latest industry trends and technologies related to AI/ML and C++ standards for embedded systems. Qualifications: Bachelor s degree or similar in Computer Science, Software Engineering, or a related field. Minimum of 2+ years of professional experience in C/C++ programming, including with embedded systems development. Proven experience with low-level programming and direct hardware interaction. Strong problem-solving skills and attention to detail. Ability to work collaboratively in a team environment. Excellent communication skills, both verbal and written. Preferred Skills: Understanding of AI/ML concepts and exposure to AI frameworks (e.g., LiteRT, ONNX Runtime, Executorch, or similar embedded inference engines). Experience with version control systems (e.g., Git). Experience in deep learning. Experience optimizing and deploying ML models on embedded devices.

Develop and implement machine learning models using Python-based frameworks. Collaborate with the AI team to build, train, and optimize models for various applications. Utilize AI libraries such as TensorFlow, PyTorch, and spaCy to develop solutions. Contribute to the design and development of AI systems that leverage large language models (LLMs) and other advanced AI techniques. Work with data preprocessing, data augmentation, and model evaluation techniques. Assist in AI model deployment and integration with applications. Required AI Skills and Knowledge: Basic understanding of AI concepts such as supervised and unsupervised learning, classification, clustering, and neural networks. Knowledge of AI libraries and frameworks TensorFlow, PyTorch, or Keras for deep learning. spaCy for natural language processing. scikit-learn for traditional machine learning. Familiarity with Large Language Models (LLMs) , such as GPT, and their applications in natural language understanding and generation. Understanding of data preprocessing techniques , feature engineering, and model evaluation metrics. Awareness of AI ethics and responsible AI development practices. Preferred Skills (Not Mandatory): Exposure to cloud-based AI development platforms (e.g., Google Cloud AI, AWS AI, or Azure AI). Familiarity with optimization techniques for AI model performance. Understanding of deep learning architectures like CNNs, RNNs, and transformers. Required Programming Skills: Python proficiency is essential. Familiarity with Python libraries like NumPy, pandas, and matplotlib for data manipulation and visualization. Experience with version control systems like Git. Training and Development Opportunities: In-depth training on AI development, including machine learning and natural language processing. Exposure to Large Language Models (LLMs) and their use cases. Hands-on experience with AI frameworks and tools like TensorFlow, PyTorch, and spaCy. Guidance on best practices for deploying and scaling AI solutions in real-world environments Basic understanding of AI concepts such as supervised and unsupervised learning, classification, clustering, and neural networks. AI ethics and responsible AI development practices. Python proficiency is essential. Python libraries like NumPy, pandas, and matplotlib for data manipulation and visualization. version control systems like Git. Large Language Models (LLMs) and their use cases.

Sberbank is looking for NLP and Speech Recognition Engineer to join our dynamic team and embark on a rewarding career journey. Analyzing customer needs to determine appropriate solutions for complex technical issues Creating technical diagrams, flowcharts, formulas, and other written documentation to support projects Providing guidance to junior engineers on projects within their areas of expertise Conducting research on new technologies and products in order to recommend improvements to current processes Developing designs for new products or systems based on customer specifications Researching existing technologies to determine how they could be applied in new ways to solve problems Reviewing existing products or concepts to ensure compliance with industry standards, regulations, and company policies Preparing proposals for new projects, identifying potential problems, and proposing solutions Estimating costs and scheduling requirements for projects and evaluating results

We are looking for a Machine Learning Operations Engineer to join our team, to design, build, and integrate ML Ops for large-scale, distributed machine learning systems, focusing on cutting-edge tools, distributed GPU training, and enhancing research experimentation. About SatSure: SatSure is a deep tech, decision Intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action, creating an impact for the other millions, focusing on the developing world. We want to make insights from Earth observation data accessible to all. Join us to be at the forefront of building a deep tech company from India that solves problems for the globe. Roles Responsibilities: Architect, build, and integrate end-to-end life cycles of large-scale, distributed machine learning systems i.e., ML Ops, using cutting-edge tools/frameworks. Develop tools and services for the explainability of ML solutions. Implement distributed cloud GPU training approaches for deep learning models. Build software/tools that improve the rate of experimentation for the research team and extract insights from it. Identify and evaluate new patterns and technologies to improve the performance, maintainability, and elegance of our machine learning systems. Lead and execute technical projects to completion. Communicate with peers to build requirements and track progress. Mentor fellow engineers in your areas of expertise - Contribute to a team culture that values effective collaboration, technical excellence, and innovation. Collaborate with engineers across various functions to solve complex data problems at scale. Qualification: 5 - 8 years of professional experience in implementing the MLOps framework to scale up ML in production. Master s degree or PhD in Computer Science, Machine Learning / Deep Learning domains Must-have: Hands-on experience with Kubernetes, Kubeflow, MLflow, Sagemaker, and other ML model experiment management tools, including training, inference, and evaluation. Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.) Proficiency with ML model training frameworks (PyTorch, PyTorch Lightning, Tensorflow, etc.). Experience with GPU computing to do data and model training parallelism. Solid software engineering skills in developing systems for production. Strong expertise in Python. Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent. Experience working with cloud data processing technologies (S3, ECR, Lambda, AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.). Having Geospatial / Remote sensing experience is a plus. Competencies: Excellent debugging and critical thinking skills. Excellent analytical and problem-solving skills. Ability to work in a fast-paced, team-based environment. Benefits: Medical Health Cover for you and your family, including unlimited online doctor consultations Access to mental health experts for you and your family Dedicated allowances for learning and skill development Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves Twice a year appraisal Interview Process: Intro call Assessment Interview rounds (ideally up to 3-4 rounds) Culture Round / HR round

: As a Banking Data Analyst, you will play a critical role in our clients' data-driven decision-making processes. You will work closely with marketing teams, product managers, and other stakeholders to understand their data needs and provide relevant analyses. Your expertise in SQL, marketing analytics, and banking domain knowledge will be essential to your success. Responsibilities : - Perform in-depth data analysis using SQL to extract and analyze banking data. - Develop and maintain reports and dashboards to track key performance indicators (KPIs). - Identify trends and patterns in banking data to provide actionable insights. - Analyze marketing campaign performance and provide recommendations for optimization. - Segment customer data to identify target audiences for marketing initiatives. - Develop and implement customer lifetime value (CLTV) models. -

Senior AI Engineer Generative AI Applications About Eucloid: Eucloid Data Solutions is a fast-growing AI-consulting firm that enables business growth for its clients through advanced Data Analytics, Machine Learning and Data engineering. Eucloid offers bespoke, full- stack and data- driven approach to solving highly complex and large-scale business problems for some of the biggest Fortune-500 organizations. Eucloid has presence across multiple continents & countries, most notably in US, India, Sweden & Indonesia. Eucloid has deep partnerships with leading Data & Cloud vendors in the industry. These range from Marketing Cloud solutions (Adobe, Twilio, Google), Customer Data Platforms (Segment, TreasureData, Adobe), Cloud Vendors (Amazon, Microsoft, Google), Machine Learning (H2O.ai, Tensorflow) and Data Products (Snowflake, Databricks, Confluent). Eucloid is also an early adopter and a strong believer in Opensource platforms like DBT, Airflow & Superset. We take immense pride in our team. We are comprised of high-performing, ambitious, diverse and highly accomplished individuals with educational backgrounds from Top-tier institutes such as IITs/NITs/BITS/DTU/IIMs, World-class Consulting, Analytics, Product & Tech orgs such as Walmart/American Express Accenture/Sapient/EXL/Noon/Citibank/Samsung. About Co-founders: Raghvendra Kushwah Raghvendra is a veteran in Business consulting with 19+ years of experience in firms like Accenture Strategy and Cognizant Business Consulting. In his last role at Accenture, he led an independent business for Accenture in India and managed a large team for analytics consultants. He is B.Tech. (IIT Delhi), MBA (IIM Lucknow) and LLB (Faculty of Law, Delhi University). Anuj Gupta Anuj has led large, diverse Products & Engineering teams with leading tech companies like Adobe and Amazon for 20+ years. In his last role at Amazon, he led a team of 50+ Engineers & 10+ Product Managers for Amazon APAC geos. He is B.Tech. (IIT Delhi) and MBA (ISB Hyderabad). About The Role: We are looking for a high-energy tech-savvy individual for the role of Senior AI Engineer- GenAI at Eucloid. The candidate will solve complex problems, picking up new technologies and working at the cutting edge of innovation. The candidate is expected to lead following work-streams: Develop and optimize Python applications for AI-driven products Build and integrate LLM-based applications with structured and unstructured data Work with large datasets, AI pipelines, and model inference APIs Collaborate with AI researchers and engineers to translate ideas into production-ready solutions Stay ahead of emerging AI technologies and contribute to continuous innovation Background and Skills: Undergraduate Degree in any quantitative discipline such as engineering, science or economics from a Top-Tier institution. 5+ years of experience in Python-based product development Strong foundation in data structures, algorithms, and system design Proven problem-solving ability you love tackling complex technical challenges Hands-on experience with APIs, backend development, and cloud platforms (AWS/GCP/Azure) Experience in AI, ML, or NLP is a bonus, but a strong aptitude to learn AI frameworks quickly is what matters most Exposure to LangChain, OpenAI APIs, or vector databases (advantageous, but not mandatory) The role offers a very attractive compensation (Base + Bonus) and is based out of Chennai. Interested Candidate Can Share their Resume at chandershekhar.verma@eucloid.com Regards Eucloid

Research in Nokia Standards (NSD) comprises fundamental systematic research of an exploratory nature for developing new products and services as well as disruptive technologies superseding conventional approaches. It covers the provision of a comprehensive understanding of scientific insights, specifically leading to (pre-) standardization of ideas and concepts for 6G technologies and beyond. In light of the recent advancements in artificial intelligence (AI) and data monetization, 6G will be the first mobile system built around and for datafirst, 6G will be the first generation of fully AI-native mobile systems where new AI features will enhance traditional solutions. Secondly, 6G will be designed according to a data-driven approach, where quantitative data and measures collected in past releases will help in shaping the design of 6G. Thirdly, 6G will be conceived to convert the massive data generated by mobile systems into valuable and monetizableinformation. You must have: Strong technical background in data science and modern data management techniques. Solid knowledge of data analysis techniques to analyze data generated in wireless systems to optimize their performance. Proven experience in data engineering methods to represent data including hands-on experience in developing data management and AI tools. Excellent written and interpersonal communication skills. Leadership and collaborative mindset with the ability to work autonomously. Strong professional ethics, open communication, and ability to rectify mistakes quickly. It would be nice if you also had: Knowledge of language processing techniques (NLP, GenAI, transformers) including hands-on experience of the tools. Experience in simulation of dynamic systems, especially for wireless communication systems (link and/or system level). Hands-on experience with AI/ML techniques applied to wireless communication. Proven software development skills with C/C++ programming language. Proven track record of innovation like publications in top conferences and journals. Drive data science progress in 6G technology and build the next generation mobile systems around modern data management approaches. Drive progress as a technical lead, contributing to new products, processes, and standards on data science for future 6G systems. Work with a world-class team to drive 6G technologies in global standardization. Carry out specialized activities/projects, demonstrating adaptability in complex business environments. Communicate within and outside the team, influencing others to accept new concepts and practices.

We are looking for a talented and highly motivated engineer to help advance our effort on creating the most efficient Multi-Model LLM models, with a specific focus on creating value for Enterprises. The candidate will be responsible for training/finetuning of MLLM models, developing prototype solutions to IBM z17 AIU hardware, working closely with IBM AIU teams, and IBM scientists in a flexible and fun environment. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise * 5+ years programming and hands on experience in python * Experience with Finetuning Multi-Model LLM models and internals of training stacks * Experience with Pytorch and FSDP * Exposure to lare scale distributed training tuning * Exposure to working with both text and image datasets Preferred technical and professional experience Exposure to Hugging Face Ecosystem, Trasnformer Models, Vision Models, and Diffusion Models Exposure to distributed foundation model training BTech/Masters/PhD in Computer Science or allied fields

Gen AI Engineer Job Description: Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) Work on tasks involving language modeling, text generation, understanding, and contextual comprehension. Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. Build and deploy AI applications on cloud platforms – any hyperscaler Azure, GCP or AWS. Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility Handle data preprocessing, augmentation, and generation of synthetic data. Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) Develop and Maintaining AI Pipelines Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Ensure the robustness, efficiency, and scalability of AI systems. Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience Strong foundation in machine learning, deep learning, and computer science. Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). Experience with natural language processing (NLP) and computer vision is a plus. Ability to work independently and as part of a team. Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions Should be able to bring new ideas and innovative solutions to our clients

Data Science professional with a proven track record in training Engineering, IT, Diploma, Polytechnic and Technical candidates. With over a 7 yrs of experience in Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing, Specialise in delivering industry-oriented, hands-on training that equips candidates with the technical proficiency required in today's data-driven world.

Role & responsibilities Qualification & Experience: As per AICTE norms for 7th Pay Commission First Class in Bachelor's and Masters degree in the relevant branch of Engineering/Technology. Roles and Responsibilities: Deliver lectures, tutorials, and laboratory sessions in the assigned engineering subjects. Assist in curriculum development and contribute to the preparation of academic plans. Support students in their project work, assignments, and technical skill development. Participate in department-level academic and administrative activities. Engage in continuous research and publish papers in peer-reviewed journals and conferences. Guide and mentor students in academics, co-curricular, and placement activities. Attend faculty development programs and stay updated with new teaching methods and technologies. Maintain discipline and academic decorum within the institution. Preferred candidate profile Candidates with a Ph.D. from reputed institutions such as IITs, with a strong academic and research background, proven publication record, and a commitment to excellence in teaching and innovation, will be given preference.

Build and deploy scalable ML models and MLOps pipelines in collaboration with data scientists Required Candidate profile 6–12 yrs in ML development, Python, model tuning, and enterprise AI deployment.