24 Lstms Jobs

Role & responsibilities Impact Based Forecasting Collaborate with other members of the IT team, meteorologists, hydrologists, GIS specialists, and disaster risk management experts within RIMES to ensure the development of IBF DSS. Develop AI models (e.g., NLP, computer vision, reinforcement learning) Integrate models into applications and dashboards. Ensure model explainability and ethical compliance. Assist the RIMES Team in applying AI/ML models to forecast hazards and project likely impacts based on exposure and vulnerability indices. Work with forecasters and domain experts to automate the generation of impact-based products. Ensure data security, backup, and compliance with data governance and interoperability standards. Train national counterparts on the use and management of the AL, including analytics dashboards. Collaborate with GIS experts, hydromet agencies, and emergency response teams for integrated service delivery. Technical documentation on data architecture, models, and systems. Capacity Building and Stakeholder Engagement Facilitate training programs for team members and stakeholders, focusing on RIMES policies, regulations, and the use of forecasting tools. Develop and implement a self-training plan to enhance personal expertise, obtaining a trainer certificate as required. Prepare and implement training programs to enhance team capacity and submit training outcome reports. Reporting Prepare technical reports, progress updates, and outreach materials for stakeholders. Maintain comprehensive project documentation, including strategies, milestones, and outcomes. Capacity-building workshop materials and training reports. Other Responsibilities Utilize AI skills to assist in system implementation plans and decision support system (DSS) development. Utilize skills to assist in system implementation plans and decision support system (DSS) development. Assist in 24/7 operational readiness for client early warning systems such as SOCs, with backup support from RIMES Headquarters. Undertake additional tasks as assigned by the immediate supervisor or HR manager based on recommendations from RIMES technical team members and organizational needs. The above responsibilities are illustrative and not exhaustive. Undertake any other relevant tasks that could be needed from time to time. Preferred candidate profile Minimum of 3 years of experience in data engineering, analytics, or IT systems for disaster management, meteorology, or climate services. Experience in multi-stakeholder projects and facilitating capacity-building programs. Machine Learning Fundamentals: Deep understanding of various ML algorithms, including supervised, unsupervised, and reinforcement learning. This includes regression, classification, clustering, time series analysis, anomaly detection, etc. Deep Learning: Proficiency with deep learning architectures (e.g., CNNs, RNNs, LSTMs, Transformers) and frameworks (TensorFlow, PyTorch, Keras). Ability to design, train, and optimize complex neural networks. Strong programming skills in Python, with extensive libraries (NumPy, Pandas, SciPy, Scikit-learn, Matplotlib, Seaborn, GeoPandas). Familiarity with AI tools: such as PyTorch, TensorFlow, Keras, MLflow, etc. Data Visualization: Ability to create clear, compelling visualizations to communicate complex data and model outputs. Familiarity with early warning systems, disaster risk frameworks, and sector-specific IBF requirements is a strong plus. Proficiency in technical documentation and user training. Contract Duration The contract will initially be for one year and may be extended based on the satisfactory completion of a 180-day probationary period and subsequent annual performance reviews. How to Apply: Interested candidates should send your application letter, resume, salary expectation and 2 references to rimeshra-india@rimes.int by midnight of 1 October 2025, Bangkok time. Please state AI SpecialistImpact-Based Forecasting: Your Name the Subject line of the email. Only short-listed applicants will be contacted. Ms. Dusadee Padungkul Head-Department of Operational Support Regional Integrated Multi-Hazard Early Warning System AIT Campus, 58 Moo 9 Paholyothin Rd., Klong 1, Klong Luang, Pathumthani 12120 Thailand. RIMES promotes diversity and inclusion in the workplace. Well-qualified applicants particularly women are encouraged to apply.

We have a job opening for GenAI Team Lead at PibyThree Consulting Services Pvt Ltd in Mumbai. The company is a Global Cloud Consulting & Services provider specializing in Cloud Transformation, Cloud FinOps, IT Automation, Application Modernization, and Data & Analytics. PibyThree aims to make businesses successful by leveraging technology for automation and enhanced productivity. As a Gen AI lead at PibyThree, you will be responsible for building both Traditional AI/ML systems and Generative AI-based systems. The ideal candidate should have a total experience of 5 to 7 years with hands-on experience in building language models, machine learning, and AI models using industry tools, products, and Azure cognitive services. Key Responsibilities: - Highly skilled in programming with the ability to assess, analyze, and organize large amounts of data - Expertise in large language models (LLMs/LSTMs/BERT) and exposure to Anthropic AI, OpenAI, among others - Experience in building, customizing, and fine-tuning AI models through GenAI studios (OpenAI, Vertex, or Bedrock) extended via Azure, AWS, or GCP for rapid PoCs - Proficiency in completions, embeddings, edits, transcriptions, translations, and moderations across various large language models - Knowledge of LlamaIndex and LangChain - Hands-on training and fine-tuning experience with distributed OpenAI models such as DaVinci, curie, Babbage, ADA - Programming skills in R, Python, SQL, Hive, Pig, and familiarity with Scala, Java, or C++ - Deep experience in applying machine learning algorithms with a strong data science and data engineering background - Understanding of cloud technology and Cognitive Services including Vision, Speech, Language, Decision, and Search - Previous projects leveraging GenAI services like Azure OpenAI, Bedrock, or Vertex - Knowledge of text/content representation techniques, statistics, and classification algorithms Good to have: - Exposure to Dataiku - Exposure to Snowflake and/or Databricks - AWS/Azure/Google Machine Learning certifications Requirements: - Bachelor's degree preferred - 5 years of total work experience with specific experience in Artificial Intelligence (2 years), Generative AI (1 year), and Machine Learning (3 years) - Generative AI Certification preferred This is a full-time position with an in-person work location and a day shift schedule. If you meet the qualifications and are interested in this role, please fill out the Google Form provided in the job description.,

As the AI Model Development & Deployment Lead, your primary responsibility will be to design and implement cutting-edge computer vision models for various tasks such as object detection, tracking, segmentation, and action recognition. You should have expertise in architectures like YOLO (v4, v5, v8), Vision Transformers, Mask R-CNN, Faster R-CNN, LSTMs, and Spatio-Temporal Models for in-depth image and video analysis. It will be crucial to contextualize the models for challenging scenarios like poor detection due to occlusion or small, fast-moving objects by training them on diverse situations. Your role will involve identifying reasons for suboptimal model performance and developing a scalable computer vision layer adaptable to different environments. Collaborating with data scientists using frameworks like TensorFlow and Pytorch, you will drive impact across key KPIs and optimize models for real-time inference through techniques such as quantization, pruning, and model distillation. In the realm of Reinforcement Learning & Model Explainability, you will be tasked with developing and integrating reinforcement learning models to enhance decision-making in dynamic AI environments. This will involve working with Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), A3C, SAC, and other RL techniques. Furthermore, you will explore explainability methods such as SHAP, LIME, and Grad-CAM to ensure transparency and interpretability of AI-driven decisions. Additionally, engineering context-aware features from video sequences to extract temporal and spatial insights for improved model explainability and decision accuracy will be part of your responsibilities. Leading the charge in creating a Scalable Data Model for AI Model Training Pipelines, you will oversee the end-to-end data preparation process, including data gathering, annotation, and quality review before training data utilization. The focus will be on enhancing the quality and volume of training data continuously to boost model performance iteratively. Your expertise in planning the data model for future scalability, with the ability to incorporate new data elements in a modular manner, will be essential. Key Technical Skills required for this role include a proven track record in delivering AI products, hands-on experience with advanced AI models, proficiency in managing and mentoring a small team of data scientists, expertise in AI/ML frameworks like TensorFlow, PyTorch, and Keras, effective collaboration with cross-functional teams, and strong problem-solving skills in image and video processing challenges. Nice to have skills include a mindset for experimentation, iterative improvement, and testing to enhance model performance continually, staying updated with the latest AI research, and balancing experimentation with timely product delivery. Collaboration with engineering and product teams to align AI solutions with product goals and deployment of AI models into production are crucial aspects. Additionally, leadership in guiding and mentoring a team of AI scientists, taking ownership of product KPIs related to AI models, and fostering an AI-first culture focused on innovation and continuous improvement will be part of your role.,

As a Senior Data Scientist at Sapper.ai, you will play a pivotal role in driving data-driven solutions within our Application Team. Leveraging your expertise in AI and ML, you will work on developing and implementing advanced models and algorithms to extract valuable insights from data, enhance OCR capabilities, and revolutionize processes in the Insurance and Accounts Receivable sectors. You'll be working on AI platforms, which are a set of products responsible for building, training, and deploying ML models for extraction and interpretation of semi and unstructured documents using NLP and Computer vision. Additionally, you'll be involved in ML model development and building automated training pipelines that deliver high-performance models on a given data set. Collaborating with application teams, you will understand their data extraction requirements that can be solved using ML. It will also be your responsibility to educate Subject Matter Experts on ensuring high-quality data annotations and assist them in validating your ML models. Furthermore, you will participate in building APIs around your model for production and ensure that they can deliver expected accuracies and throughput requirements. To excel in this role, you should have a strong theoretical and practical knowledge of ML model development, hyper-parameter tuning, and production deployment. You must possess significant experience in building models using libraries like Tensorflow and Pytorch. Proficiency in writing code in Python is essential, along with an understanding of well-known architecture/algorithms in NLP such as Transformers, LSTMs, and GRUs. Experience in fine-tuning pre-trained models like BERT and ELECTRA for downstream tasks like NER, Classification, etc., is also required. Additionally, familiarity with Object detection using libraries like Yolo or TF object detection API and the ability to comprehend model performance/shortcomings using various metrics like F1-score, mAP, confusion matrix, etc., are crucial. Knowledge of standard packaging and deployment solutions like Tensorflow Model Server, MLflow, or ONNX, as well as practical knowledge of libraries like Numpy, Pandas, and Spacy, will be beneficial. You should also have practical knowledge of building RESTful APIs around your model using Fast/Flask API and a strong Understanding of MLOPs - Life cycle of Machine Learning Models. It would be advantageous to have knowledge of the tf.data API for building reusable training pipelines and an understanding of various model pruning techniques to maximize production throughput and minimize resource requirements needed for deployment. This job opportunity was posted by Mobeena Syed from Sapper.,

As an AI & Deep Learning Scientist at Pixxel, you will play a crucial role in developing innovative machine learning and deep learning models to harness the full potential of hyperspectral data. Your focus will be on driving impactful, data-driven projects that aim to solve complex challenges using cutting-edge technology and methodologies. Working as part of the analytics team, you will have the opportunity to: - Utilize state-of-the-art AI techniques to tackle intricate problems in imaging analytics, data fusion, and large-scale data processing. - Create multimodal AI models that combine hyperspectral data with other sensor modalities like radar, LiDAR, and weather datasets, providing valuable insights for clients across various industries. - Collaborate closely with cross-functional teams to translate business and scientific objectives into scalable, efficient, and impactful AI-powered solutions. Your responsibilities will include: - Designing and implementing advanced AI/ML models for classification, prediction, segmentation, and anomaly detection using hyperspectral data and multimodal datasets. - Integrating diverse data sources to enhance feature extraction, accuracy, and scalability. - Developing computationally efficient algorithms for large-scale, high-dimensional datasets and deploying them in production environments. - Researching and implementing state-of-the-art techniques to drive AI innovation. To excel in this role, you should possess: - Proficiency in advanced machine learning and deep learning architectures. - Strong programming skills in Python and experience with frameworks like PyTorch, TensorFlow, or PyTorch Lightning. - A solid understanding of multimodal data fusion, computer vision, and large-scale data processing. - Excellent communication skills to convey complex AI concepts and findings to both technical and non-technical stakeholders. - Proven experience in implementing cutting-edge research techniques and staying abreast of AI advancements. At Pixxel, you will enjoy benefits such as comprehensive insurance coverage, access to mental health professionals, flexible working hours, and the opportunity to collaborate with top professionals in space technology. Join us in our mission to build a health monitor for the planet through innovative hyperspectral small satellites and contribute to global phenomena detection, monitoring, and prediction across various industries. For more information about Pixxel and our work, visit https://www.pixxel.space.,

We are searching for a dedicated and proficient Robotics AI/ML Engineer to become a part of our team and contribute to the advancement of intelligent and autonomous drone systems. Your primary role will involve spearheading the development of drone software stacks, merging onboard intelligence (AI/ML) with robotic middleware (ROS/ROS2) and backend systems. The ideal candidate should possess a minimum of 1 year of practical experience in constructing real-world robotics or drone software, showcasing a strong command over ROS/ROS2, computer vision, and machine learning applied to autonomous navigation, perception, or decision-making. Your responsibilities will include: - Drone Software Development: - Construct and uphold core ROS/ROS2-based software for autonomous flight, navigation, and perception. - Develop real-time systems to manage sensor fusion, path planning, obstacle avoidance, and mission execution. - Implement algorithms for drone localization (GPS, SLAM, visual odometry) and mapping. - AI/ML Integration: - Create and train AI/ML models for perception (e.g., object detection, tracking, segmentation). - Deploy and optimize AI models on edge hardware (Jetson, Raspberry Pi, Odroid, etc.). - Collaborate on multi-camera vision, lidar fusion, and real-time inference pipelines. - System Integration & Backend Communication: - Integrate drone software with backend/cloud systems using ROSBridge, WebSockets, MQTT, or custom APIs. - Develop data pipelines for telemetry, health monitoring, and AI inference output. - Collaborate with DevOps/Backend teams to ensure seamless interface with mission control and analytics dashboards. - Testing & Simulation: - Establish and oversee simulated environments (e.g., Gazebo, Ignition) for testing flight logic and AI behavior. - Conduct real-world test flights with live data and iterative tuning of software models. Requirements: - Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or a related field. - Minimum of 1 year of experience in building autonomous systems using ROS/ROS2. - Proficiency in Python and C++ with experience in writing ROS nodes and launch files. - Experience in deploying AI/ML models for perception or control (e.g., YOLO, DeepSORT, CNNs, LSTMs). - Hands-on experience with drones or mobile robotics platforms (simulation or real-world). - Familiarity with version control (Git), Linux environments, and debugging complex robotic systems. Preferred Skills: - Experience with drone-specific stacks (PX4, ArduPilot, MAVROS). - Proficiency in edge AI deployment tools (TensorRT, ONNX, OpenVINO). - Familiarity with CV frameworks like OpenCV, TensorFlow, PyTorch. - Experience with cloud platforms for robotics (AWS RoboMaker, Azure, etc.). - Understanding of control systems (PID, MPC), SLAM, or multi-agent systems. - Knowledge of cybersecurity best practices in robotics and IoT. This is a full-time, permanent position with a day shift, fixed from Monday to Friday. The role requires in-person work in Hyderabad, Telangana. Applicants must be willing to commute or relocate to Hyderabad before commencing work. As part of the application process, candidates will be asked if they have previously worked with drones or built a drone. A minimum of 1 year of experience in Robotics AI/ML is required, and an AI/ML certification is preferred.,

You will be part of a cutting-edge crypto hedge fund that specializes in high-frequency and machine-assisted trading strategies. We are looking for an exceptional PhD-level mathematical talent to lead our quantitative research and development efforts. As a PhD Physics or Mathematics candidate with advanced mathematical expertise, you will be responsible for developing sophisticated trading algorithms and innovative financial models in the dynamic cryptocurrency markets. You should have an advanced degree (Masters/PhD) in Computer Science, AI, Machine Learning, Quantitative Finance, Mathematics, or related fields. Your key responsibilities will include designing and implementing advanced machine learning and AI-driven trading strategies, developing high-frequency trading algorithms using Python/C++, conducting quantitative research on market microstructure and trading opportunities, creating predictive models using time series analysis and stochastic calculus, analyzing complex market patterns, and developing innovative trading approaches. You will also be involved in researching, designing, and implementing AI-powered trading algorithms to predict market movements and optimize execution, developing and training machine learning models using historical and real-time market data, utilizing reinforcement learning and deep learning techniques for predictive modeling in financial markets, leveraging NLP and sentiment analysis for trading signals, optimizing AI models for real-time decision-making and high-frequency trading strategies, conducting backtesting and live simulations to evaluate model performance, and working with large-scale financial datasets using cloud-based AI/ML infrastructure. To excel in this role, you are required to have a PhD in Mathematics, Applied Mathematics, Statistics, or related quantitative field, along with advanced knowledge in Stochastic Calculus, Machine Learning/Artificial Intelligence, Game Theory, Time Series Analysis, Control Theory, and Pattern Recognition. In addition to technical expertise, we are looking for candidates with a research-driven mindset, exceptional analytical capabilities, strong problem-solving skills, ability to work independently and collaboratively, strong attention to detail, ability to thrive in high-pressure environments, critical thinking skills, rapid skill acquisition, and a creative approach to complex technical challenges. The ideal candidate for this position is passionate about applying cutting-edge mathematical research to financial markets, excited by cryptocurrency's technological and financial innovations, comfortable with self-guided research and collaborative problem-solving, and adaptable to rapidly changing technological landscapes.,

Job Description At American Express, our culture is built on a 175-year history of innovation, sharedand Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role This Position is in GSG Advanced Analytics team as part of GSG MIS COE, is looking for full time candidates as Data Science Analysts. The Advanced Analytics team works across multiple Data Science/Machine Learning portfolio of projects across GSG organization across multiple areas of Servicing. Understand the overall business perspective and help conceptualize the business problem into a Data Science/ML roadmap Have a research bend of mind and read/engage/apply new techniques and algorithms in the field to generate efficiencies/process improvements. Rigorous testing of algorithms as per business norms and delivering significant working leverage over status quo and generate value for the business. Capability of writing, debugging and compiling codes in multiple Machine Learning environment and understanding of Python stack is necessary Research focus on problem solving through NLP(Natural Language Processing) is critical. Clear application on performance testing and validation framework of machine learning models Understand and deploy mathematical foundations of cutting edge NLP techniques on varied sources of data Willingness to derive insights from terabyte sized data and capability to design scalable solutions is paramount Minimum Qualifications Proven experience of applying using Machine Learning techniques like Regression, Classification, Supervised or Unsupervised Recommenders, Deep Learning etc. Ability to work in cross functional teams Excellent data wrangling and visualization skills Hands on knowledge of SQL is expected A research mindset with a zeal to experiment new algorithms is expected Preferred Qualifications: Master's in a quantitative field (e.g., Finance, Engineering, Mathematics, Statistics Computer Science or Economics) from a top institute. A set of high impact research papers on applied NLP/ Deep Learning/ GenAI Prior experience working with Transformers/LSTMs/CNNs preferred Working knowledge of finetuning Large Language Models(LLMs) is a plus Deep knowledge of Statistics and Mathematics and ability to dissect problems from the first principle. Exposure to fields like Linear Algebra, Bayesian Statistics, Group theory is desirable Complete grip on Python environment and libraries (pandas, numpy, nltk, statsmodels, gensim, pyspark, spacy, transformers), Deep learning expertise is preferred and any of Tensorflow/Torch is preferred. We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

This role is for one of our clients in the Technology, Information, and Media industry, located in Bengaluru. As a Machine Intelligence Specialist, you will be part of a forward-thinking engineering team dedicated to building intelligent systems that leverage advanced natural language processing (NLP), computer vision, and machine learning technologies. Your primary focus will be on transforming raw data into real-world automation through innovative AI solutions. Your mission will involve designing and developing intelligent systems capable of performing tasks in NLP and computer vision domains. You will be responsible for creating robust machine learning models using tools like TensorFlow, Keras, or PyTorch, and neural architectures such as CNNs, RNNs, LSTMs, and Transformers. Additionally, you will collaborate with product, data, and engineering teams to ensure alignment between AI development and business needs, enabling the seamless integration of intelligence into products and workflows. In this role, you will deploy and scale ML models on cloud platforms like AWS, Azure, or GCP, utilizing containerization tools like Docker and Kubernetes. You will drive performance tuning, data preprocessing, A/B testing, and continuous training to maintain accuracy and production reliability. Moreover, you will implement MLOps best practices, including CI/CD pipelines for ML, model versioning, and monitoring using tools like MLflow or SageMaker, while prioritizing ethical and transparent AI practices. As a qualified candidate, you should have a minimum of 3 years of hands-on experience in designing, training, and deploying machine learning models. Proficiency in Python and ML libraries such as TensorFlow, Keras, OpenCV, scikit-learn, and Hugging Face Transformers is essential. You should also possess experience in NLP and computer vision use cases, cloud-native AI tools deployment, and knowledge of containerization and orchestration. A strong foundation in mathematics, statistics, and deep learning algorithms, along with excellent communication skills and a collaborative mindset, are required. Candidates with experience in MLOps workflows and tools like MLflow, TFX, or Kubeflow, exposure to edge AI or streaming inference systems, and an understanding of responsible AI principles and data governance will be considered favorably. If you are passionate about leveraging cutting-edge AI technologies to drive impactful solutions, this role offers an opportunity to contribute to high-impact projects and make a difference.,

As an individual contributor at Adobe's Document Cloud team in Noida, you will have the exciting opportunity to be a part of crafting innovative solutions using Machine Learning, Deep Learning, and Generative AI for PDF processing across Web, Mobile, Desktop, and Platform APIs. You will be working on methods for processing a vast amount of content and building mashups of Vision, Image Processing, NLP, and generative models to solve complex problems. In this role, you will be responsible for developing algorithms that leverage deep learning and innovative techniques in NLP and computer vision, in conjunction with traditional sophisticated solutions. You will be working on creating innovative solutions using Generative AI, Python, Machine Learning, and Data Science. Your tasks will involve building experiments, algorithms, and deploying solutions that not only deliver high accuracy but are also designed to scale effectively. Collaboration with multiple research and engineering teams will be essential to deliver AI/ML software solutions efficiently. To succeed in this role, we are looking for someone with a B.Tech in Computer Science, with a preference for an MS/PhD degree. You should have at least 3 years of hands-on experience in deep-learning models, Image processing, Vision, and/or NLP. Proficiency in writing efficient, clean, and reusable code in Python is required, along with knowledge of C++. Broad Machine Learning experience covering Data, Modelling, Metric, and Analysis of Results is crucial. Exposure to Deep Learning concepts like CNNs, LSTMs, Transformers, network architecture, network tuning, transfer learning, and multi-task learning is highly desirable, along with hands-on coding experience in pyTorch or Tensorflow. Experience in building solutions from scratch and writing maintainable code inside large existing codebases is also expected. Strong software development skills that promote code reuse among engineers and researchers are essential for this role. At Adobe, creativity, curiosity, and continuous learning are valued traits that contribute to your career growth. The company encourages employees to pursue new opportunities and offers a supportive work environment. If you are passionate about making an impact and seeking a career where ongoing feedback and growth opportunities are paramount, Adobe is the place for you.,

As a Computer Vision Engineer at RNT Health Insights, you will be at the forefront of researching, developing, and implementing spatiotemporal algorithms for detecting and delineating lesions in real-time during endoscopic video feeds. Your role will involve collaborating with a multidisciplinary team of AI researchers, gastroenterologists, and software engineers to enhance both spatial and temporal accuracy in lesion detection. You will be responsible for designing preprocessing pipelines, optimizing models, and ensuring low latency, high-performance deployment in clinical settings. Key Responsibilities - Algorithm Development: Research, develop, and implement spatiotemporal techniques combined with CNN and other spatial models for real-time lesion detection in endoscopic video streams. - Temporal Analysis: Investigate and apply state-of-the-art techniques (e.g., LSTMs, 3D CNNs) to model temporal dependencies in video-based data for improved lesion tracking and detection. - Model Integration: Integrate temporal models with existing CNN-based spatial models to create efficient, end-to-end pipelines for real-time inference during endoscopy procedures. - Preprocessing & Inference Pipelines: Design and implement robust video preprocessing (e.g., frame extraction, image enhancement, noise reduction) and inference pipelines that ensure smooth integration with endoscopic hardware and software systems. - Post-processing Optimization: Work on post-processing techniques to improve lesion localization, classification, and segmentation accuracy, and ensure consistent performance in different clinical settings. - Model Optimization: Fine-tune models for deployment on constrained hardware platforms, ensuring low-latency performance without compromising accuracy. - Collaborative Research: Collaborate with research teams to explore and incorporate cutting edge temporal models, multi-frame fusion techniques, and domain-specific innovations in medical video analysis. - Performance Benchmarking: Benchmark models against datasets, assess performance (accuracy, speed, robustness), and optimize for real-time clinical use. Qualifications And Expectations - Bachelor's/ Master's/ PhD in Computer Science, Electrical Engineering, or closely related fields with a focus on Artificial Intelligence, Machine Learning, or Computer Vision. - Strong foundation in computer vision principles, including image processing techniques, feature extraction methodologies, and neural network architectures. - Proficiency with deep learning frameworks such as TensorFlow, Keras, or PyTorch. - Proficiency in programming languages, particularly Python and C++, with the ability to write clean, efficient, and well-documented code. - Solid grasp of machine learning algorithms and methodologies, including experience with real-time inference and model optimization for deployment in resource-constrained environments. - Ability to engage with and interpret relevant scientific literature, staying updated on the latest advancements in computer vision and machine learning as they apply to medical applications. - Ability to communicate ideas clearly and effectively, both in oral and written formats. - Self-motivated individual who works well in a team, and is open to giving and receiving honest feedback. If you are passionate about computer vision and eager to contribute to cutting-edge healthcare technology, we would love to hear from you!,

At EY, you'll 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 yourself. We are counting on your unique voice and perspective to help EY become even better. Join us and build an exceptional experience for yourself and contribute to creating a better working world for all. As an EY-Consulting AI Enabled Automation - GenAI/Agentic Manager, we are seeking individuals with strong AI Enabled Automation skills who are passionate about applying AI in the process automation space, including Azure, AI, ML, Deep Learning, NLP, GenAI, large Lang Models (LLM), RAG, Vector DB, Graph DB, and Python. Responsibilities: - Develop and implement AI-enabled automation solutions aligned with business objectives. - Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals to showcase 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, integrate solutions into cloud environments (Azure, GCP, AWS), and align with business goals and user needs. - Educate the team on best practices and stay updated on the latest tech advancements to bring innovative solutions to the project. Technical Skills Requirements: - 9 to 13 years of relevant professional experience, proficiency in Python, and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. - Strong foundation in ML algorithms, feature engineering, and model evaluation. - Proficiency in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP. - Experience in GenAI technologies, LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. - Knowledge of retrieval augmented generation (RAG) and Knowledge Graph RAG. - Experience with multi-agent orchestration, memory, and tool integrations. - Experience implementing MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility). - Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. - Strong understanding of data pipelines, APIs, and distributed systems. - Ability to build observability into AI systems latency, drift, performance metrics. - Strong communication, presentation, client service, and technical writing skills in English for both technical and business audiences. - Strong analytical, problem-solving, and critical thinking skills. - Ability to work under tight timelines for multiple project deliveries. What We Offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We provide stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. While we encourage you to take personal responsibility for your career, we support your professional development in every way possible. You have the flexibility to devote time to what matters to you, in both your business and personal lives. At EY, you can be yourself, express your point of view, energy, and enthusiasm, no matter where you are in the world. This is how you can make a difference. 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.,

About the Role: We are seeking a highly motivated Data Scientist Forecasting with a strong passion for energy, technology, and data-driven decision-making. In this role, you will be responsible for developing and refining energy load forecasting models , analyzing customer demand patterns , and improving forecasting accuracy using advanced time series analysis and machine learning techniques . Your insights will directly support risk management, operational planning, and strategic decision-making across the company. If you thrive in a fast-paced, dynamic environment and enjoy solving complex data science challenges , we'd love to hear from you! Key Responsibilities: Develop and enhance energy load forecasting models using time series forecasting , statistical modeling , and machine learning techniques . Analyze historical and real-time energy consumption data to identify trends and improve forecasting accuracy. Investigate discrepancies between forecasted and actual energy usage , providing actionable insights. Automate data pipelines and forecasting workflows to streamline processes across departments. Monitor day-over-day forecast variations and communicate key insights to stakeholders. Work closely with internal teams and external vendors to refine forecasting methodologies . Perform scenario analysis to assess seasonal patterns, anomalies, and market trends. Continuously optimize forecasting models , leveraging techniques like ARIMA, Prophet, LSTMs, and regression-based models . Qualifications & Skills: 3-5 years of experience in data science, preferably in energy load forecasting , demand prediction, or a related field. Strong expertise in time series analysis , forecasting algorithms , and statistical modeling . Proficiency in Python , with experience using libraries such as pandas, NumPy, scikit-learn, statsmodels, and TensorFlow/PyTorch . Experience working with SQL and handling large datasets. Hands-on experience with forecasting models like ARIMA, SARIMA, Prophet, LSTMs, XGBoost, and random forests . Familiarity with feature engineering, anomaly detection, and seasonality analysis . Strong analytical and problem-solving skills with a data-driven mindset . Excellent communication skills, with the ability to translate technical findings into business insights . Ability to work independently and collaboratively in a fast-paced, dynamic environment . Strong attention to detail, time management, and organizational skills. Preferred Qualifications (Nice to Have): Experience working with energy market data, smart meter analytics, or grid forecasting . Knowledge of cloud platforms (AWS) for deploying forecasting models . Experience with big data technologies such as Spark or Hadoop .

As a Data Science Engineer Intern at V-Patrol AI, a dynamic and forward-thinking cybersecurity organization, you will play a crucial role in developing and implementing cutting-edge machine learning and deep learning models. Your primary focus will be on creating scalable data pipelines and generating valuable insights in real-time to counter cyber threats effectively. Your responsibilities will include designing and executing machine learning and deep learning models tailored for cybersecurity applications. Additionally, you will be involved in constructing and overseeing data pipelines for both structured and unstructured data sources such as network logs and threat feeds. Integrating APIs for model deployment and ensuring seamless real-time data flow will also be a key aspect of your role. Collaboration with software engineers, analysts, and stakeholders to support data-informed decision-making processes is essential. Monitoring model performance and optimizing them for production environments will be part of your routine tasks. Furthermore, you will be responsible for conveying your findings through informative dashboards, reports, and visualizations. To excel in this role, you should hold a Bachelor's or Master's degree in data science, computer science, statistics, or a related field. Proficiency in Python, pandas, scikit-learn, and TensorFlow/PyTorch is necessary. Hands-on experience with REST APIs, Fast API/Flask, and data preprocessing techniques is crucial. Familiarity with various ML/DL models like XGBoost, LSTMs, and Transformers is expected. Exposure to cloud platforms such as AWS/GCP, ETL tools, Docker/Kubernetes, etc., would be advantageous. While not mandatory, prior experience in cybersecurity, particularly in areas like threat detection and incident response, would be beneficial. In addition to the required skills and experience, expertise in adversarial machine learning and natural language processing (NLP) will be considered a significant advantage. Having a GitHub profile or a portfolio showcasing real-world projects in data science or cybersecurity will be a strong preference. This position is an internship opportunity that requires your presence at the designated work location.,

At EY, you'll 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 we're 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. We are looking to hire individuals with strong AI Enabled Automation skills who are interested in applying AI in the process automation space using technologies such as Azure, AI, ML, Deep Learning, NLP, GenAI, large Lang Models (LLM), RAG, Vector DB, Graph DB, and Python. 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 to demonstrate 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, integrate solutions into cloud environments (Azure, GCP, AWS, etc.), and ensure alignment with business goals and user needs. - Educate the team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project. Technical Skills Requirements: - 9 to 13 years of relevant professional experience. - Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. - Strong foundation in ML algorithms, feature engineering, and model evaluation (Must). - Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP (Must). - Experience in GenAI technologies such as LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. - Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI (Agentic Framework). - Knowledge of retrieval augmented generation (RAG) and Knowledge Graph RAG. - Experience with multi-agent orchestration, memory, and tool integrations. - Experience/implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility) Good to have. - Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. - Good understanding of data pipelines, APIs, and distributed systems. - Build observability into AI systems latency, drift, performance metrics. - Strong written and verbal communication, presentation, client service, and technical writing skills in English for both technical and business audiences. - Strong analytical, problem-solving, and critical thinking skills. - Ability to work under tight timelines for multiple project deliveries. What we offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. While we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY, you can be who you are and express your point of view, energy, and enthusiasm, wherever you are in the world. It's how you make a difference. 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.,

You are seeking a seasoned Deputy Manager/Group Manager in Advanced Analytics for the Lifesciences/Pharma domain. Your primary responsibility will be to lead a dynamic team focused on assisting clients in Marketing, Sales, and Operations through advanced data analytics. Your proficiency in ML & DL Algorithms, NLP, Generative AI, Omni Channel Analytics, and Python/R/SAS is essential. Your role involves partnering with the Clients Advanced Analytics team to identify, scope, and execute advanced analytics efforts that answer business questions, solve business needs, and add business value. You will maintain a broad understanding of pharmaceutical sales, marketing, and operations to develop analytical solutions in these areas. It is crucial to stay current with statistical/mathematical/informatics modeling methodology and justify the methods selected. You will also lead the team independently to implement & deliver complex project assignments and provide strategic leadership to build new capabilities within the group. Additionally, you will contribute to whitepapers and articles at the BU and organization level, develop and deliver formal presentations to senior clients, and possess strong interpersonal communication, teamwork, leadership, and self-management skills. You should bring an insatiable desire to learn, innovate, and challenge yourself for the benefit of patients. Eligibility criteria include a minimum of 4-10 years of experience in data analytics and 2-4 years of relevant experience in Healthcare/Lifesciences/Pharmaceutical domain. Technical skills required for this role include proficiency in Python or R for statistical and machine learning applications, expertise in various techniques like Regression, Classification Decision Trees, Text Mining, Natural Language Processing, Bayesian Models, and more. You should be able to build & train neural network architectures and have hands-on experience in NLP & NLG. Knowledge in LLMs and Cloud Platforms like Azure, AWS, GCP is essential. Exposure to big data technologies is a plus. Basic qualifications include a B.Tech/Masters in a quantitative discipline such as Applied Mathematics, Computer Science, Bioinformatics, Statistics, Ops Research, or Econometrics. Your role will involve making the impossible possible in the quest to make life better, bringing Analytics to life, and continuously learning to maximize your impact in the field.,

As a Lead Data Scientist/AI Product Owner at a reputed IT MNC in Gurgaon, your primary responsibility will be AI Model Development & Deployment, focusing on Computer Vision & Deep Learning. You will be leading the design and implementation of computer vision models for various tasks such as object detection, tracking, segmentation, and action recognition. Your expertise will include architectures like YOLO (v4, v5, v8), Vision Transformers, Mask R-CNN, Faster R-CNN, LSTMs, and Spatio-Temporal Models for image and video analysis. Additionally, you will contextualize the model for challenging situations such as poor detection through specific training on different scenarios. Another key aspect of your role will involve Reinforcement Learning & Model Explainability, where you will develop and integrate reinforcement learning models to optimize decision-making in dynamic AI environments. You will work with techniques such as Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), A3C, SAC, and other RL methods. Furthermore, you will lead the development of a Scalable Data Model for AI Model Training Pipelines, overseeing the end-to-end data preparation process, including data gathering, annotation, and quality review before training. You will focus on enhancing the quality and volume of training data to continually improve model performance and have the ability to think through the data model for future enhancements. In terms of technical skills, you are expected to have a proven track record of leading and delivering AI products, hands-on expertise with advanced AI models, experience in managing and mentoring a small team of data scientists, proficiency in AI/ML frameworks like TensorFlow, PyTorch, and Keras, effective collaboration with cross-functional teams, and strong problem-solving skills in image and video processing. Nice-to-have skills include Experimentation, Iterative Improvement and Testing, Collaboration with Engineering and Product Teams, and Team Leadership. To qualify for this role, you should have at least 10 years of hands-on experience in AI with a solid background in object detection, image and video processing, and computer vision.,

As the Manager- Data Science at Holcim, you will play a crucial role in the Groups Global Advanced Analytics CoE by enabling our Businesses for Insights Driven Operations and Decision making through the utilization of cutting edge Analytics tools and techniques. Your primary responsibility will involve working closely with Business / Domain Subject Matter Experts to understand pain points and opportunities, and develop analytical models to identify patterns and predict outcomes of key business processes. You will be required to identify the most suitable modeling techniques and apply Machine Learning and Deep Learning Algorithms to create self-correcting models and algorithms. It will be essential to collaborate with Product Development teams to industrialize AI / ML models and conduct rapid and iterative prototyping of minimum viable solutions. Additionally, you will test hypotheses on raw datasets to derive meaningful insights and identify new opportunity areas. Your role will encompass all aspects of data including data acquisition, data exploration, feature engineering, building and optimizing models, and deploying Gen AI Solutions. You will be involved in designing full stack ML solutions in a distributed computing environment such as AWS and GCP, with the possibility of developing ML solutions for deployment on the edge or mobile devices if required. To be successful in this role, you should possess a total experience of 12-15 years with at least 8 years of relevant Analytics experience. Industry Experience and knowledge, particularly in Manufacturing/ Operations Functions within the Building Material Industry, Manufacturing, Process, or Pharma sectors, is preferred. Hands-on experience in statistical and data science techniques, as well as developing and deploying Gen AI Solutions, will be critical for this position. In terms of technical skills, you should have over 8 years of hands-on experience in advanced Machine Learning & Deep Learning techniques and algorithms, such as Decision Trees, Random Forests, SVMs, Regression, Clustering, Neural Networks, CNNs, RNNs, LSTMs, and Transformers. Proficiency in statistical computer languages like Python and PySpark to manipulate data and draw insights from large datasets is essential. Experience with Cloud platforms like AWS, DL frameworks such as TensorFlow, Keras, or PyTorch, and familiarity with business intelligence tools and data frameworks will be advantageous. In addition to technical skills, leadership and soft skills are equally important for this role. You should lead by example on values and culture, be open-minded, collaborative, and an effective team player. Working in a multicultural and diverse team, dealing with ambiguity, and communicating openly and effectively with various stakeholders are key aspects of this position. Being driven for success, aspiring to a culture of service excellence, and always prioritizing customer satisfaction, people, and business are qualities that will set you up for success in this role. If you are motivated by the opportunity to make a significant impact through data-driven decisions and innovative solutions, we invite you to build your future with us at Holcim by applying for this role.,

As an experienced machine learning professional with expertise in deep learning and statistical modeling for earth observation data applications, your key responsibilities will include developing models for segmentation, object classification, crop monitoring, and disaster management. It is essential for you to have proficiency in Python, ML frameworks such as TensorFlow and PyTorch, and strong research skills. An advanced degree is required for this role. SatSure is a deep tech, decision intelligence company that focuses on agriculture, infrastructure, and climate action in the developing world. The company aims to make insights from earth observation data accessible to all. Joining SatSure means being at the forefront of building a deep tech company from India that aims to solve global problems. In this role, you will be responsible for implementing deep-learning models and frameworks for various applications in agriculture and infrastructure using earth observation data. You will design and implement performance evaluation frameworks, explore new methods for improving performance, and build model monitoring and active learning pipelines. Additionally, you will work on solving research problems related to land use and land cover (LULC), crop classification, change monitoring, and disaster management using earth observations. To qualify for this role, you should have a master's degree or PhD in Engineering, Statistics, Mathematics, or Computer Science with 5-8 years of experience in machine learning-based data product research and development. Proficiency in tools and frameworks related to computer science, probability, statistics, learning theory, and deep learning fundamentals is required. Experience with statistical modeling techniques and deep learning models like CNN, RNN, Transformers, and GANs is necessary. You should also be proficient in Python and have hands-on experience in using ML frameworks such as TensorFlow, PyTorch, PyTorch Lightning, and MxNet. Additional qualifications include the ability to design, develop, and optimize machine learning/deep learning models, knowledge of applying ML to earth observation data, and an appetite for research and implementing innovative solutions for complex problems. In addition to a challenging and rewarding work environment, SatSure offers benefits such as medical health cover for you and your family, access to mental health experts, dedicated allowances for learning and skill development, and a comprehensive leave policy. The interview process includes an introductory call, assessment, presentation, multiple interview rounds, and a culture/HR round. Join SatSure to be a part of a dynamic team that is making a positive impact on the world through innovative technology and deep learning solutions.,

You will be responsible for building deep learning models using TensorFlow/PyTorch. Collaborate with the team to ensure proper testing and deployment of the models. Demonstrate good knowledge and understanding of Deep Learning Algorithms in both NLP (LSTMs, RNNs, etc.) and Computer Vision (CNNs, etc.) domain, as well as TensorFlow and deep learning frameworks like Keras, PyTorch to solve real-life problems. Create and update documentation for the work done. Understand deep learning algorithms implementation from scratch such as LSTM, RNNs, DNNs, BI-LSTMs. Work on Computer Vision and Image processing, as well as TRANSFER LEARNING - GANs. Minimum qualifications include a Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience. Relevant internship or work experience with data analysis. Experience with statistical software (R, Python, S-Plus, SAS, or similar) and database languages (e.g. SQL) is required. Preferred qualifications include a Master's or B.Tech in relevant field. Your responsibilities will include researching on given machine learning/data science topics for writing articles for company websites. Assist with hands-on coding on Jupyter Notebook for providing code snippets in the articles. Work on short projects & assignments, deployment techniques, and design and implement machine learning, information extraction, probabilistic matching algorithms and models. Use your passion for programming and deep learning/AI skills using Python, TensorFlow, and deep learning frameworks like Keras, PyTorch to solve real-life problems. Develop AI solutions in the computer vision domain using convolutional neural networks (CNN) and a combination of deep neural networks such as CNN & RNN. Solve object detection, recognition, image classification problems using machine learning and deep learning algorithms & transfer learning methods and techniques. Use innovative & automated approaches for data annotation, labeling, and data augmentation & use active learning. Handle online code assistance, code mentoring, and education-based solutions. Perks include Certificate, Letter of recommendation, Flexible work hours, Informal dress code, 5 days a week, Free snacks & beverages.,

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology we set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation -driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Man agement Trainee -Human Resource Analytics In this role, you will act as a Technical Leader for our People Analytics projects Responsibilities Lead the People Analytics Projects Accountable for all technical details of the projects and is expected to run them independently, end to end. Constantly upskilled with latest developments in the field of Machine Learning / Deep Learning Ensure we incorporate Machine Learning / Deep Learning, as applicable. Own entire project life cycle - Data collection, Data clean up and then modelling. Adept in storyboarding project insights Qualifications we seek in you! Minimum qualifications Relevant experience in Machine Learning / Deep Learning . Preferred Qualifications/ Skills Excellent hands-on experience in Machine Learning techniques such as Decision Trees (Random Forest), Support Vector Machines, Regression (Linear & Logistic) Should have hands on experience in Deep Neural network techniques such as RNNs and LSTMs Have worked on NLP. Adept at visualizing data and presenting it to stakeholders. Good with statistical concepts such as Probability Distributions and Hypotheses testing. Should have run Machine Learning / Deep Learning projects on cloud servers and handled large datasets. Good rank on Kaggle competitions is preferred. Excellent communication (verbal & written) skills - should be adept in storyboarding project insights. Languages preferred: Python or R Needs to be independent and self-motivated and comfortable working independently. Experience in ML Ops, Airflow would be an added advantage . Why join Genpact Lead AI-first transformation - Build and scale AI solutions that redefine industries Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career &mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Skills Required Deep Learning Expertise: Strong understanding of deep learning concepts, including neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), transfer learning, etc. Proficiency in Machine Learning Frameworks: Hands-on experience with popular frameworks such as TensorFlow, Keras, PyTorch, or MXNet. Mathematics for Machine Learning: Solid knowledge of mathematical foundations, including linear algebra, probability, statistics, and optimization algorithms related to deep learning. Experience in Model Building: Ability to build, train, and optimize deep learning models for different use cases like image classification, NLP, speech recognition, etc. Content Development Skills: Experience in creating comprehensive learning materials, including video lectures, assignments, quizzes, and projects for students. Programming Proficiency: Strong knowledge of Python and libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn. Cloud and Deployment: Familiarity with deploying deep learning models on cloud platforms like AWS, GCP, or Azure. Hands-on Projects: Experience in creating hands-on projects to help students apply learned concepts practically. Pedagogy & Curriculum Development: Ability to structure and organize technical content clearly and logically to suit a range of learning levels. Communication Skills: Excellent written and verbal communication skills to explain complex technical concepts simply and effectively. Collaboration Skills: Ability to work with instructors, instructional designers, and subject matter experts to create engaging and accurate content. Prior experience in content development is preferred. Responsibilities Assist the Technical Content Developer (TCD) in creating high-quality technical content across various formats such as text, video scripts, presentations, and interactive materials. Support the TCD in researching and gathering resources to ensure the accuracy and relevance of the content. Collaborate with Subject Matter Experts (SMEs) and other team members to refine and polish content for final delivery. Contribute to developing curriculum outlines, roadmaps, and learning objectives under the guidance of the TCD. Ensure content is optimized for different learning formats, adapting materials as required. Participate in regular content reviews and provide suggestions for improvements or updates based on learner feedback. Stay updated on industry trends and assist in incorporating emerging technologies and techniques into the content. Manage smaller content projects independently while maintaining alignment with the overall curriculum goals. Job Overview Location : NxtWave Office Spaces in Hyderabad Job Type : Full-Time Working days : 5

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.