2458 Deep Learning Jobs - Page 27

Staff Engineer/Tech Lead AI/ML [ Natural Language Processing, Transformers, Gen AI, LLM, Neural Networks] The Opportunity As a Staff Engineer (MTS-6) , you will own the architecture and AI/ML systems that power both log and metrics analysis , enabling automated diagnostics and reducing triage time for QA failures, regression runs, and customer issues. Youll also help define and drive the central AI charter at Nutanix, building reusable components, model infrastructure, and scalable ML services. About the Team The Panacea team has a passionate set of engineers across India and US office. We move fast, collaborate closely, and care deeply about quality and ownership. Our mission is to deliver AI/ML-powered developer productivity tools that solve real engineering and support pain points at scale. Why Join Us Build AI-first observability tools that redefine how engineers triage and troubleshoot. Own systems that reduce hours of manual work in engineering and SRE workflows . Collaborate with a tight-knit team of high-ownership engineers who are passionate about impact and innovation. Hybrid work model that supports flexibility and deep focus. Help shape the central AI charter at Nutanix and influence future AI products across the company. Your Role AI-Powered Observability Platform : Own the vision, architecture, and delivery of Panaceas ML-based log and metrics analyzer that reduces triage time and improves engineering efficiency. AI/ML-powered Log Analyzer Tool : Use deep learning (e.g., ModernBERT ) to represent log messages, detect anomalies, group patterns, and surface actionable insights to users. Metrics Anomaly Detection Engine : Build robust ML models to detect anomalies in time-series metrics like CPU, memory, disk I/O, network traffic, service health , and moreautomatically identifying performance degradation or system regressions across distributed environments. Auto-RCA Engine : Combine log and metrics signals with graph-based correlation and LLM-powered summarization to automatically diagnose the root cause of system failures. Feedback Loop & Continuous Learning : Build infrastructure for incorporating user feedback to continuously retrain and improve anomaly detection systems. LLM Integration : Integrate LLMs for user queries, problem summarization, anomaly explanation, and contextual recommendations. Central AI Charter : Contribute to Nutanixs foundational AI platform by defining shared tooling, datasets, governance, and reusable ML components across products. Responsibilities Architect and scale ML pipelines for real-time and batch-based anomaly detection in both logs and time-series metrics. Build and fine-tune ModernBERT and other transformer-based models for log understanding, anomaly classification, and summarization. Develop unsupervised and semi-supervised ML models for detecting anomalies in system metrics (CPU, memory, network throughput, latency, etc.). Implement correlation models to connect anomalies across logs and metrics to form a cohesive RCA narrative. Own the entire ML lifecycle: data ingestion, feature extraction, model training, evaluation, deployment, and monitoring. Build explainable AI systems that increase adoption and trust within engineering, QA, and support teams. Collaborate with cross-functional stakeholders (SRE, QA, Dev) to deeply understand pain points and translate them into intelligent tooling. Drive technical excellence through code and design reviews, mentoring, and setting engineering best practices. What You Will Bring Educational Background : B.Tech/M.Tech in Computer Science, Machine Learning, AI, or related fields. Experience : 12+ years of engineering experience , including designing , developing and deploying AI/ML systems at scale. ML Expertise : Strong in time-series anomaly detection, statistical modeling, supervised/unsupervised learning. Experience building ML models for metrics data (CPU, memory, IOPS, network, etc.) using models like Isolation Forest, Prophet, LSTM, or deep autoencoders. Expertise in NLP using ModernBERT, BERT, or log classification, clustering, and summarization. Experience with LLMs for downstream tasks like summarization, root cause reasoning, or intelligent Q&A. Engineering Skills : Strong Python background, hands-on with ML libraries (PyTorch, TensorFlow, Scikit-learn), time-series frameworks, and MLOps tools. Familiar with data pipelines and serving models. Observability Knowledge : Hands-on with logs, metrics, traces, and popular monitoring tools (e.g., Prometheus, Grafana, ELK). Leadership : Ability to independently drive projects from requirements to delivery, mentor junior engineers, and deliver business impact. Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. For most roles, that will mean coming into an office a minimum of 2 - 3 days per week, however certain roles and/or teams may require more frequent in-office presence. Additional team-specific guidance and norms will be provided by your manager.

Location: Bangalore Experience: 6 - 14 Years Notice Period: Immediate Joiners and Serving NP JD: AI and Machine Learning minimum 2 years of hands on experience in Artificial Intelligence, Machine Learning , Deep Learning , Computer Vision projects, products, and systems. Experience of working on ML algorithms, DL models (NLP based models). Vector Databases, Graph Databases etc. Generative AI Familiarity with Generative AI models – including LLMs , RAG Approach, communication flow in both approaches, multimodal usage, open-source models from Hugging face, Lang chain frameworks , Vector DB (atleast one DB should be well known in terms of indexing, storing the embeddings, extracting the answers), Prompts, Context based prompts etc. Experience with transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion ) Cloud Platforms: At-least experience of working on one of cloud platforms: AWS Sagemaker, Azure OpenAI, GCP, Google Cloud Vertex AI, IBM WatsonX etc. Thorough knowledge on the various types of Models, F1 score, accuracy, training the models, tuning of models (with hyperparameters & all other techniques), possible statistical models and their fitment, model deployment, data pre/post processing. Knowledge should come out of their practical experience from their projects (no theoretical answers) either using cloud native services or open-source s/w. HW Platforms: At-least experience of working on Intel or Nvidia platforms (CPU+GPU)s Software Engineering – agile development practices, requirements, design, architecture, debugging and validation of software products/projects Experience building commercial grade software, with much of that experience in a large scale, high availability service. Programming Experience – Python, C, C++, C#, Java etc. Working knowledge of Distributed Systems and Cloud Technologies. Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch) to develop production-grade quality product Ability to debug, read code and work on a large and increasing codebase Good understanding of statistics, linear algebra, and probability theory Excellent problem-solving skills and the ability to work independently and collaboratively Design and architecture: Ability to understand scalable, performant, secure, and efficient AI systems and solutions. Collaboration: Ability to work seamlessly with cross-functional teams, including data scientists, project engineers, delivery (customer), and practice teams. Communication: Ability to clearly convey technical concepts to both technical and non-technical audiences

You will develop, optimize, and deploy state-of-the-art generative models for diverse applications, including text generation, image synthesis, and audio processing This role requires expertise in computer vision, machine learning, deep learning, and MLOps, with hands-on experience in GANs, VAEs, Transformers, and Diffusion Models You will actively contribute to building AI tools for CGI animation and VFX pipelines, enabling scalable, creative, and efficient workflows across departments including Asset Development, Rigging, Animation, Layout, Lighting, FX, Compositing, Editorial, and Rendering Design, develop, train, and optimize generative models (GANs, VAEs, Diffusion Models, Transformer Models) across text, image, audio, and video domains: 3D Reconstruction Human Pose Estimation Multimodal Learning Speech-Driven Animation Python and C++ for AI and pipeline integration

IT Education Centre is looking for Data Science Trainer to join our dynamic team and embark on a rewarding career journey Curriculum Development: Designing and creating training programs or courses covering a wide range of data science concepts and tools, tailored for different skill levels, from beginners to advanced learners Instruction and Delivery: Conducting training sessions, workshops, or classes to teach data science methodologies, tools, and best practices This involves explaining complex concepts in an understandable manner and using practical examples and exercises Material Creation: Developing educational materials, including presentations, slides, handouts, coding exercises, and datasets, to support the learning process Hands-on Practice: Providing opportunities for students to apply theoretical concepts through hands-on projects or real-world case studies, enabling them to gain practical experience Mentoring and Support: Offering guidance, feedback, and support to students or trainees throughout their learning journey, helping them overcome challenges and advance their skills Staying Updated: Keeping abreast of the latest trends, tools, and techniques in data science and integrating new developments into training materials and curriculum Assessment and Evaluation: Assessing the progress of trainees through assignments, tests, or projects, and providing constructive feedback to help them improve Engagement and Collaboration: Collaborating with other trainers, educators, or professionals in the field to exchange knowledge, share resources, and enhance training methodologies

Early part of a World Class product doing unimaginable engineering magic Design, implement and train state-of-the-art deep learning and Generative AI models for visual content. Research and evaluate the performance of the latest deep learning architecture to solve challenging real problems. Design innovative AI based Image rendering pipelines for pre-processing and post-processing images About you Solid code-writing skills in Python Experience working with generative models APIs including Dalle, Stable Diffusion, GPT3 Have experience with working on atleast one of the following deep learning models: Transformers, GANs, Diffusion based models. Solid experience working with image libraries like OpenCV and/or PIL Some experience fine-tuning and training AI models on Cloud for different use-cases Bonus points Experience Deploying and Inferencing AI models using cloud Experience with real and synthetic large-scale data curation for real problems A track record of publications and contributions to the machine learning and computer vision communities If you dont have some of above, but still feel youre exceptional, you can still reach out

Lead and oversee AI research and development activities at Unstudio, with a specific focus on training and deploying deep learning and generative AI models for visual content Responsible for deployment and scalability of AI models on the cloud services like AWS/GCP AI is moving very fast. Stay up-to-date with the latest advancements in deep learning and AI research Collaborate closely with cross-functional teams, including product, engineering, and design, to integrate AI capabilities seamlessly into our suite of products. Provide technical leadership and guidance in AI-related decision-making processes. About you Solid background (3 + years) in AI research and development, with specific focus on training and optimising generative AI and deep learning models Strong in Python and relevant frameworks such as TensorFlow or PyTorch. Previous demonstrable experience fine tuning /training LLMs Diffusion based models Proven expertise in deploying AI models on the cloud like GCP/AWS/Azure, ensuring scalability and performance. Experience working with image and video data and relevant libraries PIL, OpenCV, FFMPEG etc. Passionate about pushing the boundaries of AI and its application in design, with a deep understanding of the intersection between technology and creativity.

Job Description: Principal Data Scientist (Gen AI) Key Responsibilities: 8+ years of experience in data science, including 2+ years of hands-on experience working with and fine-tuning pre-trained LLMs (e.g., GPT, LLaMA) and diffusion models (e.g., Stable Diffusion, DALL-E, or MidJourney). Proficient in Python with a solid understanding of supervised and unsupervised learning techniques and strong hands-on expertise with machine learning packages such as scikit-learn, XGBoost, LightGBM, etc. Proficiency in deep learning frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers for fine-tuning and deploying LLMs and generative AI models. Proven experience in designing and implementing pipelines leveraging Vector/Graph Databases (e.g. Pinecone, FAISS, Neo4j) and Retrieval-Augmented Generation (RAG) for large-scale, efficient information retrieval and model integration. Experience with prompt engineering to optimize LLM performance for specific tasks, including designing and refining prompts to improve model outputs, enhancing coherence, relevance, and creativity in generated content. Hands-on experience with big data technologies such as PySpark for processing and analyzing massive datasets at scale. Exceptional problem-solving skills, with a proven ability to tackle complex challenges in language understanding, multimodal AI, and Generative AI projects. Nice-to-Have: Experience leveraging agents in LLMs (e.g., LangChain or similar frameworks) to build dynamic, multi-step workflows for reasoning, planning, and decision-making tasks. Familiarity with MLOps/LLMOps principles, including CI/CD pipelines, monitoring tools (e.g., MLflow, Kubeflow). Experience with containerization technologies (e.g., Docker, Kubernetes) and serverless architectures for scalable AI deployments. Knowledge of RESTful APIs, message brokers (e.g., RabbitMQ, Kafka), and event-driven architectures to build robust, real-time AI applications. Hands-on experience with cloud platforms such as AWS or Azure AI for deploying large-scale ML models. Knowledge of ethical AI principles, including fairness, transparency, and bias mitigation in AI systems. A Masters or Ph.D. in Statistics, Machine Learning, Mathematics, Computer Science, or a related quantitative field.

AI / Machine Learning / Data Science part time Work from Home (Any where in world) Warm Greetings from Excel Online Classes, We are a team of industry professionals running an institute that provides comprehensive online IT training, technical support, and development services. We are currently seeking AI / Machine Learning / Data Science Experts who are passionate about technology and can collaborate with us in their free time. If you're enthusiastic, committed, and ready to share your expertise, we would love to work with you! Were hiring for the following services: Online Training Online Development Online Technical Support Conducting Online Interviews Corporate Training Proof of Concept (POC) Projects Research & Development (R&D) We are looking for immediate joiners who can contribute in any of the above areas. If you're interested, please fill out the form using the link below: https://docs.google.com/forms/d/e/1FAIpQLSdvut0tujgMbBIQSc6M7qldtcjv8oL1ob5lBc2AlJNRAgD3Cw/viewform We also welcome referrals! If you know someone—friends, colleagues, or connections—who might be interested in: Teaching, developing, or providing tech support online Sharing domain knowledge (e.g., Banking, Insurance, etc.) Teaching foreign languages (e.g., Spanish, German, etc.) Learning or brushing up on technologies to clear interviews quickly Upskilling in new tools or frameworks for career growth Please feel free to forward this opportunity to them. For any queries, feel free to contact us at: excel.onlineclasses@gmail.com Thank you & Best Regards, Team Excel Online Classes excel.onlineclasses@gmail.com

We are seeking for a proactive and technically skilled AI & Automation specialist to help us transform and automate our existing manual operations including customer support ( via calls, email and chat) , email queries, accounts, and follow-ups.

Skills Required Minimum 1-4 years of experience in content development. Strong understanding of neural networks, CNNs, RNNs, LSTMs, GANs, transformers, and other advanced architectures. Expertise in Python and popular Deep Learning frameworks like TensorFlow, PyTorch, and Keras. Hands-on experience building, training, and deploying Deep Learning Models. Experience working with real-world datasets for image recognition, NLP, time series forecasting, and other domains. Knowledge of pre-trained models and transfer learning techniques. Responsibilities Lead a team of Associate technical content developers to ensure timely and high-quality content creation. Develop high-quality, industry-relevant content on Deep Learning concepts, including neural networks, CNNs, RNNs, GANs, transformers, and other advanced topics. Incorporate hands-on projects and real-world datasets to provide practical learning experiences. Understanding of how to develop content to meet various learner needs and styles. Collaborate with Subject Matter Experts (SMEs) to ensure technical accuracy and relevance of the content. Design curriculum outlines, learning objectives, and roadmaps for comprehensive technical programs. Stay updated with the latest industry trends to incorporate cutting-edge topics and technologies into the content. Review and revise content regularly based on learner feedback and emerging educational strategies. Act as a bridge between content development and product teams, driving feature development and design improvements to support immersive and practical learning experiences. Monitor and report on the progress of content development to ensure alignment with organisational goals. Job Overview Location : NxtWave Office Spaces in Hyderabad Job Type : Full-Time Working days : 5 days a week

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

Best Enterprises , a leader in packaging automation and industrial vision systems, is expanding its R&D team. We are looking for a Computer Vision Engineer with strong programming skills and a passion for applying AI/ML in visual inspection and defect detection . Freshers with strong programming skills and a passion for computer vision are welcome to apply. Programming Work Develop image processing applications using C++ and OpenCV . Apply AI/ML/Deep Learning models to detect complex defects and classification tasks. Build real-time and low-cost industrial applications using compact embedded vision systems. System Integration Work Select and procure cameras, lenses, lights, computers, embedded PCs . Source bowl feeders, linear conveyors , and material handling systems. Collaborate with mechanical engineers to finalize camera and light positioning . Interface vision systems with PLCs, encoders, and industrial sensors . Required Skills Proficient in OpenCV and image processing techniques. Strong coding skills in C++ (or C# ). 2 years of hands on experience in Computer vision Preferred Skills In-depth understanding of AI / ML / Deep Learning for vision tasks. Hands-on with integrating AI models into real-time industrial vision applications. Experience with TensorFlow or PyTorch or YOLO or ONNX is a plus. Familiarity with NVIDIA Jetson or Raspberry Pi or Coral TPU based deployments. Interview Process The selection process includes a phone interview followed by an in-person assessment of programming skills

Conducting classroom Training on programming skills Creating a positive and engaging learning environment A passion for teaching and helping students achieve their career goals Strong knowledge of SQL. Python, Data Science, ML, DL, NLP, Power Bi

WhatsApp at 8076971094 Should have an experience ranging from 0-3 years of strong technical and Analytical Skills Strong proficiency in Python with a solid understanding of OOP principles. Experience with one or more blockchain frameworks (Solidity, Web3.py, Hardhat, Truffle) Research knowledge of IoT protocols and edge platforms Understanding of network security, encryption standards, etc. Proficiency in machine learning frameworks like Scikit-learn, TensorFlow, or PyTorch. Familiarity with deep learning architectures: CNNs, RNNs, Transformers. Experience working with or fine-tuning LLMs (e.g., GPT, LLaMA, Falcon).

We have an exciting and rewarding opportunity for you to take your AI ML career to the next level. As a Senior Software Engineer in the Self Service Enablement team, you will lead the development and innovation of agentic applications using LLM technologies. You will work closely with a talented team to design scalable, resilient applications with strong observability, contributing to JP Morgan Chases mission of delivering exceptional self-service solutions. Your role will be pivotal in driving innovation and enhancing the user experience, making a difference in the lives of our clients and the wider community. Job Responsibilities Develop solutions related to data architecture, ML Platform as well as GenAI platform architecture, provide tactical solution and design support to the team and embedded with engineering on the execution and implementation of processes and procedures Serve as a subject matter expert on a wide range of ML techniques and optimizations. Provide in-depth knowledge of distributed ML platform deployment including training and serving. Create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques. Gain Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines. Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team. Own end to end code development in python/Java for both proof of concept/experimentation and production-ready solutions. Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks and collaborate with product and engineering teams to deliver tailored, science and technology-driven solutions. Drives decisions that influence the product design, application functionality, and technical operations and processes. Required Qualifications, Capabilities, and Skills Formal training or certification on AI ML concepts and 3+ years applied experience Solid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Good understanding in deep learning frameworks such as PyTorch or TensorFlow. Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search). Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Practical cloud native experience such as AWS Preferred Qualifications, Capabilities, and Skills Experience with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker. Exposure to agentic frameworks such as Langchain, Langgraph, RASA, Parlant, Decagon. We have an exciting and rewarding opportunity for you to take your AI ML career to the next level. As a Senior Software Engineer in the Self Service Enablement team, you will lead the development and innovation of agentic applications using LLM technologies. You will work closely with a talented team to design scalable, resilient applications with strong observability, contributing to JP Morgan Chases mission of delivering exceptional self-service solutions. Your role will be pivotal in driving innovation and enhancing the user experience, making a difference in the lives of our clients and the wider community. Job Responsibilities Develop solutions related to data architecture, ML Platform as well as GenAI platform architecture, provide tactical solution and design support to the team and embedded with engineering on the execution and implementation of processes and procedures Serve as a subject matter expert on a wide range of ML techniques and optimizations. Provide in-depth knowledge of distributed ML platform deployment including training and serving. Create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques. Gain Experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines. Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team. Own end to end code development in python/Java for both proof of concept/experimentation and production-ready solutions. Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks and collaborate with product and engineering teams to deliver tailored, science and technology-driven solutions. Drives decisions that influence the product design, application functionality, and technical operations and processes. Required Qualifications, Capabilities, and Skills Formal training or certification on AI ML concepts and 3+ years applied experience Solid understanding of using ML techniques specially in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Good understanding in deep learning frameworks such as PyTorch or TensorFlow. Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search). Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Practical cloud native experience such as AWS Preferred Qualifications, Capabilities, and Skills Experience with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker. Exposure to agentic frameworks such as Langchain, Langgraph, RASA, Parlant, Decagon.

Responsibilities: Analyze structured and unstructured data. Build and deploy machine learning models for text classification task. Develop visualization tools and dashboards to communicate findings to business partners. Collaborate with business, product and engineering teams to clearly articulate data insights into actionable recommendations. Skills: Bachelor s or Master s degree in Computer Science, Statistics, Mathematics, Data Science, or related field. 3+ years of experience in a data science or analytics role. Hands on experience in GCP, AWS or Azure cloud platform. Familiarity with GCP Vertex AI is a plus. Strong ability in developing and deploying ML solutions. Proficient in Python, scikit learn, PyTorch, and TensorFlow, with expertise in machine learning, NLP, and deep learning model development and optimization. Strong understanding of data patterns, feature engineering, and model lifecycle from design to validation, tuning, and scaling. Exposure to big data tools (e.g. BigQuery, Spark) and MLOps practices for scalable, production-grade ML pipelines.

About Us - Attentive.ai is a leading provider of landscape and property management software powered by cutting-edge Artificial Intelligence (AI). Our software is designed to optimize workflows and help businesses scale up effortlessly in the outdoor services industry. Our Automeasure software caters to landscaping, snow removal, paving maintenance, and facilities maintenance businesses, while our Accelerate software provides end-to-end solutions for all commercial landscape maintenance and construction jobs through automated workflows. Trusted by top US and Canadian sales teams, we are backed by renowned investors such as Sequoia Surge and InfoEdge Ventures." Position Description: We are looking for a Software Engineer to join our engineering team and help us develop and maintain various software products. As a Back-end developer at Attentive, you will help us in the development of new smart web applications and you will be involved in the development of our internal ML/AI and processing pipelines. We offer an inspiring environment full of young people with a lot of ambition. You get freedom to implement your own designs, solutions and creativity Responsibilities : Take complete, end to end ownership of development and production pipelines of internal tools and consumer-facing products. Ensure high performance, reliability, and availability of hosted deep learning and geoprocessing services. Translate high-level tasks and product requirement documents into technical design documents and scalable, maintainable and readable codebases Develop and implement high and low-level system design for newer projects Develop scripts and set up the infrastructure for monitoring and logging for all deployed software Evaluate, profile and improve the functionality of existing systems Coordinate with internal teams to understand data processing pipelines and provide technical solutions Effectively lead teams of junior developers and ensure high code quality through code reviews, automated linting, etc. Requirements & Qualifications: 3 years of work experience comprising of Backend (preferably Django), Frontend and Software Design/Architecture Knowledge of messaging services like Apache Kafka, RabbitMQ Experience in developing data processing pipelines Experience in distributed web services development and chaining Internally motivated, able to work proficiently both independently and in a team environment Understanding of cloud services like AWS and GCP Experience with DevOps technologies such as Docker, Kubernetes, Jenkins, CI/CD, etc Good To Haves Experience with PostGIS or any other geo-database Experience in developing production versions of deep learning applications Understanding of Geographic Information Systems and related terminologies is preferred Experience working in both start-up and enterprise culture

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at Amazon Music Search team is seeking an experienced Applied Scientist who will join a team of experts in the field of machine learning, and work together to break new ground in the world of understanding and classifying different forms of music, and creating interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval. Youll work in a collaborative environment where you can pursue applied research, with many peta-bytes of data, work on problems that haven t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. Youll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web. Use machine learning, deep learning, LLMs and NLP techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazons data to help automate and optimize key processes Design, development and evaluation of highly innovative models for predictive learning Work closely with software engineering teams to drive model implementations and new feature creations Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Research and implement novel machine learning and statistical approaches A day in the life Imagine being part of an agile team where your ideas have the potential to reach millions. Picture working on highly impactful consumer-facing products, where every single team member is a critical voice in the decision-making process. Envision being able to leverage the resources of a Fortune-500 company within the atmosphere of a start-up. Welcome to Amazon Music, where ideas are born and come to life as Amazon Music Unlimited, Prime Music, and so much more. 3+ years of building machine learning models for business application experience PhD, or Masters degree and 6+ years of applied research experience Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc.

We are looking to engage an AI expert or consultant who can support us with a code review specifically aimed at making our models for Open Source . This would be a temporary engagement for around 1 to 2 months. Kindly share relevant profiles. We are looking for this requirement to be filled up immediately however Skillset Requirement: Python, Pytourch, Tensor Flow, Machine Learning, Deep Learning, Code Review Location: Hyderabad (Work from Office Only) Duration of Engagement: 1-2 Months Minimum Experience required: 3-5 Years

Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you ll see and hear the results of your work everywhere, from movie theaters to smartphones. We continue to revolutionize how people create, deliver, and enjoy entertainment worldwide. To do that, we need the absolute best talent. We re big enough to give you all the resources you need, and small enough so you can make a real difference and earn recognition for your work. We offer a collegial culture, challenging projects, and excellent compensation and benefits, not to mention a Flex Work approach that is truly flexible to support where, when, and how you do your best work. Dolby s research division is looking for a researcher to join Dolby s research efforts to develop the next generation of AI based multimodal technologies. The candidate will work with Dolby s world-class audio and vision experts to invent new multimedia analysis, processing and rendering technologies to drive new interactive and immersive experiences. As a part of an international team, the candidate will work on ideas exploring new horizons in multimodal processing, analysis, and interactivity. The researcher is responsible for performing fundamental new research, transferring technology to product groups, and drafting patent applications. Summary Dolby s research division is currently looking for a talented, self-motivated researcher to push the boundaries of the state-of-the-art in multi-media technologies. An ideal candidate would have a strong background in HCI and deep learning, both in terms of conceptual understanding, as well as practical experience. A core aspect of this role involves being able to keep up to date with the literature, implement, and innovate. Consequently, knowledge or experience in any/all the following are helpful: Human-computer interaction techniques and application of deep learning to this area Diffusion, autoregressive, or other generative models. Self-supervised, contrastive learning, auto-encoders. Audio, image, or text applications Source separation, text-to-speech, music synthesis, image segmentation, image captioning, question answering, language models, etc. Latent space exploration, navigation, control and alignment techniques The role will involve prototyping inspiring experiences that explore a complement of modalities. These technologies will be used to extend immersion and interaction, the candidate should be willing to explore empirical refinement of the user experience. The ideal candidate has experience in developing real-time applications delivering multi-modal experiences and/or human-computer interfaces with generative AI involvement. Main responsibilities: Prototype and demonstrate multimodal, interactive and immersive user experiences. Work closely with other domain experts to refine and execute Dolby s technical strategy in artificial intelligence and machine learning. Use deep learning to create new solutions and enhance existing applications. Push the state-of-the-art and develop intellectual property. Transfer technology to product groups and draft patent applications. Advise internal leaders on recent deep learning advancements in the industry and academia to further influence research direction and business decisions. Requirements: Ph.D. in computer science or similar, with a focus on deep learning. Knowledge in audio, video, 3D, or text processing is desirable. Strong publication record, with publications in top domain-specific or general machine learning conferences e.g., ACM CHI, NeurIPS, ICLR, ICML, ACL, CVPR, ICASSP. Good knowledge about current machine learning literature. Highly skilled in Python and one or more popular deep learning frameworks (TensorFlow or PyTorch). Ability to envision new technologies and turn them into innovative products, Creativity. Good communication skills. All official communication regarding employment opportunities at Dolby will come from an official dolby.com email address. We will never request payment as part of the hiring process. If you receive a suspicious message, please verify its authenticity before responding.

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.

Key Responsibilities: Machine Learning (ML): Design, build, and deploy ML pipelines for structured and unstructured data. Conduct feature engineering , model selection, and hyperparameter tuning. Evaluate model performance using industry-standard metrics and improve accuracy. Collaborate with data engineering teams to ensure clean and accessible data for model training. Apply supervised, unsupervised, and reinforcement learning techniques as per use case. Natural Language Processing (NLP): Develop NLP pipelines for text classification, sentiment analysis, entity recognition, summarization , etc. Leverage libraries like spaCy, NLTK, Hugging Face Transformers, and Gensim . Preprocess and tokenize large corpora using advanced NLP methods. Implement solutions for multi-lingual, domain-specific text data challenges. Integrate NLP services with applications or workflows. Large Language Models (LLM): Fine-tune and deploy LLMs (e.g., GPT, LLaMA, BERT, Falcon, Mistral ) on custom datasets. Use prompt engineering and retrieval augmented generation (RAG) to build intelligent systems. Optimize inference performance and latency for production-level deployment. Stay updated with the latest in GenAI, foundation models, and transformer architectures. Work on use cases like chatbots, question answering, summarization, content generation , and semantic search . Required Skills: Proficiency in Python , PyTorch or TensorFlow , and data science libraries ( scikit-learn , pandas , NumPy ). Experience with NLP frameworks and transformer-based architectures . Exposure to LLM model training/fine-tuning using tools like Hugging Face, LangChain, or OpenAI API. Familiarity with MLOps , model versioning, and deployment using Docker/Kubernetes. Understanding of vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings.

Description: We are looking for a highly skilled Data Scientist to join our AI Center of Excellence (CoE) in Pune. This role involves working on complex financial datasets, building machine learning models, and delivering data-driven insights that support business decisions and product innovation. The ideal candidate should be hands-on, analytical, and passionate about solving real-world problems through data. Requirements: Required Skills & Experience: 4–6 years of proven experience in Data Science, preferably in the finance or FinTech industry. Strong coding skills in Python, R, and SQL. Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. Solid foundation in statistical modeling, data analysis, and deep learning. Familiarity with cloud platforms like AWS, Azure, or GCP. Proficiency in data visualization tools such as Power BI, Tableau, or Matplotlib. Excellent communication skills to effectively present data-driven insights. Preferred Qualifications: Master’s or Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field. Exposure to NLP, generative AI, or large language models. Experience with MLOps practices for deploying and monitoring models. This position is based in Pune and requires immediate joining. Hybrid or in-office availability is expected based on project needs. Job Responsibilities: Key Responsibilities: Analyze large-scale financial datasets to extract meaningful insights and trends. Develop and deploy machine learning models for predictive analytics and decision support. Translate business challenges into data science problems and propose appropriate solutions. Collaborate with product and business teams to build and implement data-driven features and tools. Communicate analytical findings clearly through visualizations and presentations for non-technical stakeholders. Continuously explore and adopt emerging tools, techniques, and best practices in AI/ML. What We Offer: Exciting Projects: We focus on industries like High-Tech, communication, media, healthcare, retail and telecom. Our customer list is full of fantastic global brands and leaders who love what we build for them. Collaborative Environment: You Can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities! Work-Life Balance: GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules, opportunities to work from home, and paid time off and holidays. Professional Development: Our dedicated Learning & Development team regularly organizes Communication skills training(GL Vantage, Toast Master),Stress Management program, professional certifications, and technical and soft skill trainings. Excellent Benefits: We provide our employees with competitive salaries, family medical insurance, Group Term Life Insurance, Group Personal Accident Insurance , NPS(National Pension Scheme ), Periodic health awareness program, extended maternity leave, annual performance bonuses, and referral bonuses. Fun Perks: We want you to love where you work, which is why we host sports events, cultural activities, offer food on subsidies rates, Corporate parties. Our vibrant offices also include dedicated GL Zones, rooftop decks and GL Club where you can drink coffee or tea with your colleagues over a game of table and offer discounts for popular stores and restaurants!

Responsibilities: Deliver training on data analyst and data science. Train freshers and working Professionals on data science, data analyst, business analyst, financial analyst. Train teams on data science principles through interactive sessions Annual bonus

Educational Bachelor of Engineering Service Line AI & Automation Service Line Responsibilities Data collection and preparationCollect and prepare data for training and evaluating LLMs. This may involve cleaning and processing text data, or creating synthetic data Model developmentDesign and implement LLM models. This may involve choosing the right architecture, training the model, and tuning the hyperparameters Model evaluationEvaluate the performance of LLM models. This may involve measuring the accuracy of the model on a held-out dataset, or assessing the quality of the generated text Model deploymentDeploy LLM models to production. This may involve packaging the model, creating a REST API, and deploying the model to a cloud computing platform. Responsible AIShould have proficient knowledge in Responsible AI and Data Privacy principles to ensure ethical data handling, transparency, and accountability in all stages of AI development. Must demonstrate a commitment to upholding privacy standards, mitigating bias, and fostering trust within data-driven initiatives. Experience in working with ML toolkit like R, NumPy, MatLab etc.. Experience in data mining, statistical analysis and data visualization Additional Responsibilities: Ability to develop value-creating strategies and models that enable clients to innovate, drive growth and increase their business profitability Good knowledge on software configuration management systems Awareness of latest technologies and Industry trends Technical and Professional : Primary skills:Technology-Artificial Intelligence -Generative AI-Computer Vision,Technology-Big Data-Natural language processing(NLP),Technology-Machine Learning-Python Preferred Skills: Technology-Big Data-Natural language processing(NLP) Technology-Machine Learning-Python Technology-Artificial Intelligence-Computer Vision Technology-Machine Learning-Generative AI