217 Cnn Jobs - Page 4

-1Role & responsibilities AI/ML Engineer About the Role: We are building an AI-powered food recognition system for our fitness and nutrition app. The goal is to enable users to scan meals, identify food items (especially Indian cuisine), and get an instant nutritional breakdown (calories/macros). Were looking for an AI/ML Engineer who can take full ownership of this project from dataset creation and model development to backend integration and deployment. Responsibilities: 1 Dataset Preparation Collect or curate labeled food image datasets (focus on Indian meals) Organize images into structured folders for training Perform data augmentation, resizing, normalization 2 Model Development Choose and fine-tune a CNN model (e.g., ResNet, EfficientNet, MobileNet) Apply transfer learning for food classification (20+ categories) Optimize for high accuracy and convert to TensorFlow Lite (optional for mobile) 3 Training & Evaluation Train the model on Google Colab, local GPU, or cloud Evaluate using metrics like accuracy, F1 score, and confusion matrix Iterate to improve results based on testing 4 Backend Integration Build REST APIs using FastAPI to serve model predictions Accept image uploads and return predicted food labels with confidence scores Integrate predictions with existing MySQL database 5 Deployment & Support Save and deploy the trained model (.h5 or .tflite) Collaborate with the mobile team (React Native) to connect the API or run on-device predictions Ensure performance, scalability, and reliability in production Mandatory Skills: ML/AI TensorFlow / Keras / PyTorch, Transfer Learning, CNNs Image Processing ImageDataGenerator, Pillow/OpenCV, image augmentation Backend FastAPI (REST APIs) Deployment Model saving/loading, TFLite conversion Database Basic integration with MySQL Cloud/Infra Google Colab, AWS EC2 Versioning Git, GitHub, proper code structuring Preferred candidate profile

Job Title: Data Scientist Location: Sector V, Salt Lake, Kolkata (3 days WFO , 2 days WFH) Notice: Maximum 15 days (Immediate Joinees Preferred) Education Requirements: Full-time Masters degree in Computer Science, AI/ML, Data Science, Statistics, or Mathematics from a reputed institution. PhD preferred (Not Mandatory) Experience: Minimum 3 years of relevant industry or research experience (for Masters) 1 to 2 years for PhD holders Key Skills: Strong knowledge of Data Structures and Algorithms Advanced programming skills in Python ( Mandatory ) Working knowledge of C++ ( Good to have ) Hands-on experience with AI/ML, Deep Learning (CNN, RNN), LLMs, classification, clustering Good understanding of algorithm design and development Familiarity with reinforcement learning, computer vision, or NLP is an advantage Job Responsibilities: Design and develop robust AI/ML algorithms to solve complex technical problems Build, test, and optimize ML models for high performance Prepare clear documentation and present technical work to stakeholders Work in a collaborative team for integration, productisation, and deployment Stay updated with latest AI/ML trends and contribute new ideas Good to Have: 4G/ 5G Domain Experience Knowledge of Cloud Research publications, patents, or open-source contributions

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.

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

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

Job Description: AI Developer Fresher Location: Bangalore Company: MagicBox Cybersec Pvt. Ltd. Employment Type: Full-time | Entry-level Position Overview: We're MagicBox Cybersec, and we're building a powerful Cybersecurity in a Box a fully automated, AI- driven platform to detect threats, prevent intrusions, and ensure compliance. We're on the hunt for fresh minds who think logically, solve problems creatively, and love building smart systems that make the digital world safer. Key Responsibilities: • • • • Build and train AI/ML models for threat detection, anomaly detection, and behavioral analysis. Develop intelligent automation pipelines for cybersecurity operations. Work closely with AI & security experts to integrate models into real-time environments. Apply your skills in Python, ML libraries, and Linux to develop scalable solutions. Qualifications: • • Education o B.E./B.Tech/M.Tech in CS, AI, Data Science, or related fields o 01 year experience. Freshers are welcome! Skills o o o o o o o o o o Strong analytical and logical reasoning skills. Passion for AI/ML and interest in Cybersecurity. Familiarity with Python and frameworks like TensorFlow, PyTorch, or Scikit-learn. Comfortable in Linux environments (CLI, scripting). Project experience in AI/ML (college / online / hackathon / personal). Supervised/Unsupervised learning. Classification algorithms. Decision Trees. Random Forest. Deep Learning Algorithms(ANN, RNN, CNN, LSTMP, LLMs). Additional Qualifications: • • • Basic understanding of cybersecurity workflows (IDS, SIEM, etc.) Exposure to NLP or AI-based automation tools Git, Bash, or scripting experience What We Offer: • • • Work on cutting-edge AI Cybersecurity projects from day one. Mentorship and rapid learning opportunities. Flat structure, startup vibe, innovation-friendly culture. Ready to join us? Apply Now! Send your CV and a short note on your AI interests to: careers@magicboxcysec.com

About the Team Our Data Science team is the Avengers to Meeshos S.H.I.E.L.D ???. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. Weve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. Our typical day involves dealing with fraud detection, inventory optimisation, and platform vernacularisation. As Lead Data Scientist, you will navigate uncharted territories with us, discovering new paths to creating solutions for our users.?? You will be at the forefront of interesting challenges and solve unique customer problems in an untapped market. But wait theres more to us. Our team is huge on having a well-rounded personal and professional life. When we aren't nose-deep in data, you will most likely find us belting Summer of 69 at the nearest Karaoke bar, or debating who the best Spider-Man is: Maguire, Garfield, or Holland? You tell us ?? About the Role Love deep data? Does innovative-thinking describe you? Then you may be our next Lead Data Scientist. In this role youll be the Dumbledore to our team of wizards - our junior data scientists. You will be responsible for transforming scattered pieces of information into valuable data that can be used to achieve goals effectively. You will extract and mine critical bits of information and drive insightful discussions that result in app innovations. What you will do Own and deliver solutions across multiple charters by formulating well-scoped problem statements and driving them to execution with measurable impact Mentor a team of data scientists (DS2s and DS3s), helping them with project planning, execution, and on-call issue resolution Design and optimize key user journeys (e.g., Reseller Experience, Search, Fraud Systems) by identifying user intents and behavioral patterns from large-scale data Collaborate with machine learning engineers and big data teams to build scalable ML pipelines and improve inference performance Continuously track and improve model performance using state-of-the-art (SOTA) techniques and libraries Lead experimental design for usability improvements and user growth, leveraging statistical rigor Contribute to system-level thinking by enhancing internal tools, frameworks, and libraries to improve team efficiency and code quality Partner with engineering to ensure data reliability, compliance with security/PII guidelines, and integration of models into production systems Proactively explore new areas of opportunity through research, data mining, and academic collaboration, including publishing and attending top-tier conferences Communicate findings, plans, and results clearly with DS, product, and tech stakeholders, and create technical documentation consumable by both DS and engineering teams Conduct research collaborations with premier colleges and universities Attend conferences and publish research papers What you will need A Bachelor's degree in Computer Science, Data Science, or a related field; a Masters is a plus 6--8 years of experience in data science with a strong track record of building and deploying ML solutions at scale Deep understanding of core ML techniques supervised, unsupervised, and semi-supervised learning along with strong foundations in statistics and linear algebra Exposure to deep learning concepts and architectures (e.g., CNNs, RNNs, Transformers) and their practical applications Proficiency in Python and SQL, with experience in building data pipelines and analytical workflows Hands-on experience with large-scale data processing using Apache Spark, Hadoop/Hive, or cloud platforms such as GCP Strong programming fundamentals and experience writing clean, maintainable, and production-ready code Excellent analytical and problem-solving skills the ability to extract actionable insights from messy and high-volume data Solid grasp of statistical testing, hypothesis validation, and common pitfalls in experimental design Experience designing and interpreting A/B tests, including uplift measurement and segmentation Ability to work closely with product and engineering teams to translate business goals into scalable ML or data solutions Bonus points for: Experience with reinforcement learning or sequence modeling techniques Contributions to ML libraries, internal tools, or research publications

2+ years of ML + NLP experience. Programming in Python. Knowledge of SQL and NoSQL databases. Expert ability to write robust code in Python. Experience working with structured and unstructured data including data extraction, integration, and normalization. Very fluent in ML frameworks/libraries like Tensorflow, Pytorch, ONNX, Scikit Learn, Keras, Spacy. Expert skill at manipulating data frames using Pandas and arrays using NumPy. Good To Have: Experience with big data frameworks such as Spark and Hadoop. Experience with containerizing applications using docker. Roles and Responsibilities Understanding business objectives and formulating the problem as a Machine Learning problem. In-depth knowledge of various NLP domains such as entity extraction, topic modeling, knowledge graphs, parsing, question answering, etc and linking with domain specific dictionaries. Expertise in a variety of Deep Learning architectures including RNN, CNN, LSTMs, Transformer, and Transfer Learning. Excellent background in Machine Learning (generative model, discriminative model, neural network, regression, classification, clustering, etc.) and conversational AI (chatbots). Implement cutting edge CV techniques in image classification, object detection, semantic segmentation, sequence modeling, etc. using frameworks such as OpenCV. Hands-on experience in any public cloud environment (AWS, GCP or Azure). Ability to build robust data processing and analytics pipelines. Operationalize ML models into production environment(s). Strong knowledge of software fundamentals, data structures and algorithms. Strong analytical and problem-solving skills. Quick learner passionate about Machine Learning and Data Science.

Why this job matters We are searching for a proficient AI/ML engineer who can help us to extract value from our data. The resource will be responsible for E2E processes including data collection, cleaning & pre-processing, training of the models and deployment in all production and non-production environments. What youll be doing Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress. Analysing the ML algorithms that could be used to solve a given problem and ranking them by their success probability. Analysing the ML algorithms that could be used to solve a given problem and ranking them by their success probability. Verifying data quality, and/or ensuring it via data cleaning. Supervising the data acquisition process if more data is needed. Defining validation strategies Defining the pre-processing or feature engineering to be done on given data. Defining data augmentation pipelines. Training models and tuning their hyperparameters. analysing the errors of the model and designing strategies to overcome them. Perform statistical analysis and fine-tuning using test results. Train and retrain systems when necessary. Strong knowledge on model deployment pipeline MLOPS and knowledge of AWS/GCP deployment. Skills Required Proven experience (4 or more years) as a Machine Learning Engineer/ Artificial Intelligence Engineer or similar role. Solving business problems using Machine Learning algorithms, Deep Learning/Neural Network algorithms, Sequential model development, and Time series data modelling. Experience with Computer Vision techniques, Convolutional Neural Networks (CNN), Generative AI, and Large Language Models (LLMs) Experience with deploying models using MLOps pipelines. Proficiency in handling both structured and unstructured data, including SQL, BigQuery, and DataProc. Hands-on experience with API development using frameworks like Flask, Django, and FastAPI. Automating business and functional operations using AIOps. Experience with cloud platforms such as GCP and AWS, and tools like Qlik (Added advantage) Understanding of data structures, data modelling and software architecture. Expertise in visualizing and manipulating big datasets. Deep knowledge of math, probability, statistics and algorithms. Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas. Knowledge in R or Java is a plus. Proficiency in TensorFlow or Keras and OpenCV is a plus. Excellent communication skills. Team player. Outstanding analytical and problem-solving skill. Familiarity with Linux environment. Low to medium familiarity with JIRA, GIT, Nexus, Jenkins etc is a plus. Minimum educational qualification: BE/B.Tech or similar degree in relevant field. The skills youll need Troubleshooting Agile Development Database Design/Development Debugging Programming/Scripting Microservices/Service Oriented Architecture Version Control IT Security Cloud Computing Continuous Integration/Continuous Deployment Automation & Orchestration Software Testing Application Development Algorithm Design Software Development Lifecycle Decision Making Growth Mindset Inclusive Leadership

Role Overview: Youll lead efforts in developing, training, and deploying machine learning models with a focus on data processing and computer vision. Using your expertise in Python, OpenCV, and other advanced tools, you will work on complex data science projects and help us push the boundaries of AI technology. Data Modelling & Processi Leverage OpenCV and advanced computer vision techniques for tasks like image recognition, object detection, and OCR. Model Development: Design, build, and train machine learning models using deep learning frameworks such as TensorFlow, PyTorch, and Keras. Computer Vision Projects: Leverage OpenCV and advanced computer vision techniques for tasks like image recognition, object detection, and OCR. ML Algorithms & Frameworks: Implement ML algorithms and leverage frameworks for NLP, computer vision, and other AI projects. Testing & Experimentation: Conduct machine learning tests and experiments, refining models based on performance metrics. API Development: Utilize Flask or Django to create APIs for model integration with applications. Data Annotation & Augmentation: Apply data augmentation techniques for robust model performance, especially in image-based datasets. Collaboration & Reporting: Work closely with cross-functional teams and provide detailed insights on model performance and data metrics. Technical Skills Required: Programming Languages: Proficiency in Python, with strong skills in C/C++ for performance-based applications. ML Frameworks: Expertise in TensorFlow, PyTorch, and Keras. Libraries & Tools: Strong command of OpenCV, Numpy, Scikit-learn, and Matplotlib. Data Handling & Processing: Hands-on experience with data processing tools such as Pandas and SQL. Natural Language Processing (NLP): Experience with NLP techniques using libraries like NLTK. Web Scraping & Automation: Familiarity with Beautiful Soup for data extraction and Selenium for automation. Software Development Tools: Knowledge of Django, Flask, Jupyter Notebook, and Linux environments. Analytical Skills: Strong understanding of optimization techniques, regularization methods, and model architecture. Qualifications: Bachelors degree in Computer Science, Engineering, or a related field. 2-4 years of experience in data science, machine learning, and model development. Demonstrated expertise in computer vision and natural language processing. Strong problem-solving and communication skills for cross-functional collaboration. Why Join Us? Cutting-Edge Projects: Work on innovative AI and machine learning projects. Professional Growth: Access to training and career advancement. Dynamic Environment: Collaborate with a team passionate about data and technology.

Primary Skills: Semantic Kernel and Azure AI AgentExp min 9 month of real project experience Semantic Kernel experiencefocuses on building intelligent agents and applications by leveraging the Semantic Kernel SDK, which is an open-source framework from Microsoft that allows for the integration of AI models and services. Secondary Skills: This role involves designing and developing AI solutions, including copilots, and integrating them with enterprise data and systems using tools like Azure OpenAI, Azure AI Search

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions, ensuring that they meet quality standards. You will work with generative AI models and may also explore various domains such as deep learning, neural networks, chatbots, and image processing, contributing to innovative projects that push the boundaries of technology. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Facilitate knowledge sharing and mentorship within the team to enhance overall performance.- Continuously evaluate and improve existing processes and methodologies to drive efficiency. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Experience with cloud-based AI services and deployment strategies.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Familiarity with natural language processing techniques and tools.- Ability to design and implement scalable AI solutions. Additional Information:- The candidate should have minimum 12 years of experience in Large Language Models.- This position is based at our Kolkata office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions, ensuring that they meet quality standards. You will work with various AI models, including generative AI, deep learning, and neural networks, while also exploring innovative applications such as chatbots and image processing. Collaboration with cross-functional teams will be essential to integrate these advanced technologies into effective solutions that address real-world challenges. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge.- Continuously evaluate and improve existing processes and systems to optimize performance. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Good To Have Skills: Experience with cloud-based AI services.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Familiarity with natural language processing techniques and tools.- Experience in developing and deploying chatbots and conversational agents. Additional Information:- The candidate should have minimum 5 years of experience in Large Language Models.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Expected Notice Period : 15 Days Shift : (GMT+01:00) Europe/London (BST) Opportunity Type : Remote Placement Type: Full Time Contract for 6 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - UK's Leading AgriTech Company) What do you need for this opportunity? Must have skills required: AgriTech Industry, Large Language Models, Nvidia Jetson, Raspberry Pi, Blender, Computer Vision, OpenCV, Python, Pytorch/tensorflow, Segmentation, Extraction, Regression UK's Leading AgriTech Company is Looking for: Location: Remote Type: 6 months contract Experience Level : 35 Years Industry: Agritech | Sustainability | AI for Renewables About Us We're an AI-first company transforming the renewable and sustainable agriculture space. Our mission is to harness advanced computer vision and machine learning to enable smart, data-driven decisions in the livestock and agricultural ecosystem. We focus on practical applications such as automated weight estimation of cattle , livestock monitoring, and resource optimization to drive a more sustainable food system. Role Overview We are hiring a Computer Vision Engineer to develop intelligent image-based systems for livestock management, focusing on cattle weight estimation from images and video feeds. You will be responsible for building scalable vision pipelines, working with deep learning models, and bringing AI to production in real-world farm settings . Key Responsibilities Design and develop vision-based models to predict cattle weight from 2D/3D images, video, or depth data. Build image acquisition and preprocessing pipelines using multi-angle camera data. Implement classical and deep learning-based feature extraction techniques (e.g., body measurements, volume estimation). Conduct camera calibration, multi-view geometry analysis, and photogrammetry for size inference. Apply deep learning architectures (e.g., CNNs, ResNet, UNet, Mask R-CNN) for object detection, segmentation, and keypoint localization. Build 3D reconstruction pipelines using stereo imaging, depth sensors, or photogrammetry. Optimize and deploy models for edge devices (e.g., NVIDIA Jetson) or cloud environments. Collaborate with data scientists and product teams to analyze livestock datasets, refine prediction models, and validate outputs. Develop tools for automated annotation, model training pipelines, and continuous performance tracking. Required Qualifications & Skills Computer Vision: Object detection, keypoint estimation, semantic/instance segmentation, stereo imaging, and structure-from-motion. Weight Estimation Techniques: Experience in livestock monitoring, body condition scoring, and volumetric analysis from images/videos. Image Processing: Noise reduction, image normalization, contour extraction, 3D reconstruction, and camera calibration. Data Analysis & Modeling: Statistical modeling, regression techniques, and feature engineering for biological data. Technical Stack Programming Languages: Python (mandatory) Libraries & Frameworks: OpenCV, PyTorch, TensorFlow, Keras, scikit-learn 3D Processing: Open3D, PCL (Point Cloud Library), Blender (optional) Data Handling: NumPy, Pandas, DVC Annotation Tools: LabelImg, CVAT, Roboflow Cloud & DevOps: AWS/GCP, Docker, Git, CI/CD pipelines Deployment Tools: ONNX, TensorRT, FastAPI, Flask (for model serving) Preferred Qualifications Prior experience working in agritech, animal husbandry, or precision livestock farming. Familiarity with Large Language Models (LLMs) and integrating vision + language models for domain-specific insights. Knowledge of edge computing for on-farm device deployment (e.g., NVIDIA Jetson, Raspberry Pi). Contributions to open-source computer vision projects or relevant publications in CVPR, ECCV, or similar conferences. Soft Skills Strong problem-solving and critical thinking skills Clear communication and documentation practices Ability to work independently and collaborate in a remote, cross-functional team Why Join Us? Work at the intersection of AI and sustainability Be part of a dynamic and mission-driven team Opportunity to lead innovation in an emerging field of agritech Flexible remote work environment

Expected Notice Period: 30 Days Shift: (GMT+05:30) Asia/Kolkata (IST) Opportunity Type: Remote What do you need for this opportunity Must have skills required: Start-up Experience, Python, Ml frameworks, Statistical analysis, CNNs, Machine Learning, Computer Vision, AI models Leegality is Looking for: What you'll do As an ML Engineer, you will develop solutions to interesting technical problems, explore exciting growth opportunities, and have a real impact on our product. To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software. Responsibilities: Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Transforming data science prototypes and applying appropriate ML algorithms and tools. Solving complex problems with multi-layered data sets and optimizing existing machine learning libraries and frameworks. Developing ML algorithms to analyze huge volumes of historical data to make predictions. Running tests, performing statistical analysis, and interpreting test results. Exposure to generative AI (LLM) based ML architectures Experienced in working with CNN. Knows how to train and fine-tune CNN-based models. Documenting machine learning processes. Requirements: 1+ years of relevant experience in Machine Learning Engineering. Advanced proficiency with Python. Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture. Superb analytical and problem-solving abilities. Great communication and collaboration skills. Preferences: Start-up experience is good to have. Willing to join immediately, ideally. Female candidates are preferred Interview Process - Technical Round 1 - ML Fundamentals, NLP models Assessment Technical Round 2 - Discussion on the assignment submitted modify it according to the requirements Round 3 - with the Tech Lead - Tech Managerial - Past projects in-depth knowledge of ML

Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build business case for technological investments to be made for future needs and to remain competitive Ensure that billing and utilization of team members is maximized throughout the year

Primine Software Private Limited is looking for Machine Learning Engineer to join our dynamic team and embark on a rewarding career journeyA Machine Learning Engineer is responsible for designing, building, and maintaining systems that use artificial intelligence (AI) and machine learning (ML) algorithms to solve complex problems. 1.Developing and implementing ML algorithms: The Machine Learning Engineer develops and implements machine learning algorithms to solve specific problems, such as natural language processing, computer vision, or predictive modeling.2.Building data pipelines: The Machine Learning Engineer is responsible for building data pipelines that collect, store, and preprocess data used in machine learning algorithms.3.Creating and maintaining ML infrastructure: The Machine Learning Engineer is responsible for creating and maintaining ML infrastructure, including hardware, software, and cloud platforms, that support the development and deployment of ML models.4.Testing and validating ML models: The Machine Learning Engineer tests and validates ML models, ensuring that they are accurate, robust, and scalable.5.Troubleshooting ML systems: The Machine Learning Engineer troubleshoots ML systems, identifying and resolving issues related to performance, accuracy, and scalability.6.Deploying ML models: The Machine Learning Engineer deploys ML models in production environments, integrating them with other software systems and ensuring that they are reliable and scalable.

PRIMARY RESPONSIBILITIES: Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress Managing available resources such as hardware, data, and personnel so that deadlines are met Analysing the ML algorithms that could be used to solve a given problem and ranking them by their success probability Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world Verifying data quality, and/or ensuring it via data cleaning Supervising the data acquisition process if more data is needed Finding available datasets online that could be used for training Defining validation strategies Defining the pre-processing or feature engineering to be done on a given dataset Defining data augmentation pipelines Training models and tuning their hyper parameters Analysing the errors of the model and designing strategies to overcome them Deploying models to production Key SKILL: Proficiency with a deep learning framework such as TensorFlow Proficiency with Python and basic libraries for machine learning such as scikit-learn, pandas and pytorch Expertise in visualizing and manipulating big datasets Deep knowledge of Math (Linear Algebra), CNN and algorithms Run models in cloud environments Google or Azur EXPERIENCE: 4-5 years of experience in machine learning related projects. EDUCATION AND EXPERIENCE REQUIREMENTS: Bachelors or Masters degree in a computer field LOCATION: Vadodara JOB TIMING: UK timings, 2:30pm to 11:30pm (March-October), 3:30pm to 00:30am (October-March)

Hands on Experience:- NLP/LLM Hugging Face, YOLO, CNNs, Stable Diffusion ML algorithms (regression, decision trees, clustering) Model training/fine-tuning using real-world datasets FastAPI,Flask,Django Docker, Kubernetes Cloud experience

What will your role look like Design AI solutions using both traditional ML and GenAI approaches based on problem needs Lead end-to-end implementation of ML projects including data preparation, model development, deployment, and monitoring Build GenAI-based applications using LLMs, embeddings, and multi-step reasoning frameworks (e.g., LangChain, LangGraph) Conduct research and proof-of-concepts to evaluate emerging GenAI models and techniques Guide and mentor junior engineers; review designs, architecture, and code quality Develop fine-tuned and instruction-tuned LLMs using platforms like Hugging Face, OpenAI, Cohere, etc. Build agentic AI systems involving tool use, memory, and reasoning frameworks Ensure AI models are robust, explainable, and cost-efficient in production Collaborate with stakeholders to understand business goals and translate them into technical solutions Communicate complex AI concepts to both technical and non-technical audiences. This is a strategic role where you will play a key part in shaping our AI offerings, guiding teams, and solving complex problems using both modern and established AI techniques. Why you will love this role Besides a competitive package, an open workspace full of smart and pragmatic team members, with ever-growing opportunities for professional and personal growth Be a part of a learning culture where teamwork and collaboration are encouraged, diversity is valued and excellence, compassion, openness and ownership is rewarded. We would like you to bring along Experienced AI/ML Engineer with a strong background in both traditional Machine Learning and Generative AI. Experience in classical AI/ML and 23 years in GenAI, total 10 years of experience with the ability to design, research, and build scalable AI solutions across domains. 67 years in traditional ML/DL, including regression, classification, clustering, NLP, time series forecasting, and deep learning techniques such as feedforward networks, CNNs, RNNs, LSTMs, GRUs, and attention-based models for structured, unstructured, and sequential data 23 years in Generative AI (LLMs, embeddings, RAG, fine-tuning, prompt engineering) Experience with Python, scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers Understanding of ML lifecycle: data wrangling, feature engineering, model training, evaluation, and deployment Deep experience with LLMs such as GPT, LLaMA, Mistral, Claude, or Gemini and tools like LangChain, LangGraph, and LLamaIndex Experience building agentic AI solutions (e.g., AutoGPT, ReAct, CrewAI, BabyAGI) Proficiency with vector databases (FAISS, Pinecone, Weaviate, Chroma) and embedding models (OpenAI, Cohere, BGE, etc.) Excellent communication and presentation skills Strong research mindset with the ability to quickly learn and adapt to new GenAI technologies Ability to assess trade-offs between classic and generative AI techniques and recommend the best-fit approach

About The Business - Tata Electronics Private Limited (TEPL) is a greenfield venture of the Tata Group with expertise in manufacturing precision components Tata Electronics (a wholly owned subsidiary of Tata Sons Pvt Ltd ) is building Indias first AI-enabled state-of-the-art Semiconductor Foundry This facility will produce chips for applications such as power management IC, display drivers, microcontrollers (MCU) and high-performance computing logic, addressing the growing demand in markets such as automotive, computing and data storage, wireless communications and artificial intelligence Tata Electronics is a subsidiary of the Tata group The Tata Group operates in more than 100 countries across six continents, with the mission 'To improve the quality of life of the communities we serve globally, through long term stakeholder value creation based on leadership with Trust Job Responsibilities - Develop and implement advanced machine learning models to solve complex business problems, translating analytical findings into tangible business solutions Develop computer vision algorithms and deploy them to production environments, ensuring seamless integration with existing systems and infrastructure Understand business requirements by working closely with domain experts to define problem statements and success metrics that align with organizational goals Collaborate with data engineers to design and implement efficient data pipelines that support model development, training, and deployment Analyse large datasets to extract meaningful insights, identify patterns, and drive data-informed decision making across the organization Work with the mother company's (PSMC) AI team to understand use cases, align strategies, and leverage existing resources and expertise Optimize and fine-tune machine learning models for scalability, ensuring they can handle increased data volumes and maintain performance under varying conditions Monitor model performance post-production deployment, implementing systems to track key metrics and ensure adherence to established performance standards Ensure data quality and integrity by implementing rigorous validation processes and addressing data gaps or inconsistencies before model development Communicate technical findings to non-technical stakeholders through clear visualizations, reports, and presentations that translate complex analysis into actionable insights Essential Attributes - Willing to work in semiconductor domain and building cutting edge AI/ML system Proficiency in Computer vision/ Python code writing Ability to understand and debug code Understanding of Linux OS Experience in working with large dataset and improving data pipelines Deep Understanding of CNN, RNN, DNN ?s Mathematics Experience in computer vision model deployments Excellent teamwork skills to work closely with Manufacturing, Quality, and IT teams Ability to communicate technical issues and solutions effectively to cross-functional teams Enthusiasm for learning new AI/ML technologies, tools Qualifications - BE/ ME in Computer science, Machine Learning, Electronics Engineering, Applied mathematics, Statistics

B. Tech / B.E. from a Tier-1 Institution (IITs, IISc, IIITs, BITS, NITs or similar institutions), preferably in Computer Science, IT, Electronics Engineering, Electrical Engineering, Mathematics or any other related field. Minimum 2+ years of hands-on experience in machine learning, deep learning, or computer vision roles. Strong expertise in deep learning frameworks such as PyTorch, TensorFlow, and Keras. In-depth knowledge of CNNs, Transformers, Siamese networks, contrastive learning, and embedding space analysis. Proficient in Python and experienced with largescale data processing tools like Spark, Dask, or Hadoop. Prior experience working with biometric, or image datasets (face, iris, fingerprint) is desirable. • Strong understanding of data cleaning, clustering (e.g., DBSCAN, K-Means), anomaly detection, and unsupervised learning. Knowledge of privacy-preserving techniques such as federated learning, differential privacy & homomorphic encryption is a plus. Job Profile Design and develop state-of-the-art deep learning models for biometric recognition (facial, fingerprint, iris) and fraud detection using convolutional neural networks (CNNs), transformers, and hybrid architectures. Lead the design of end-to-end AI pipelines: data ingestion, pre-processing, model training, evaluation, and deployment in production environments. Conduct thorough error analysis A/B testing, and performance evaluations to identify weaknesses and improve recognition accuracy and system efficiency. Architect scalable data pipelines for image and biometric signal cleaning, feature extraction, clustering, and deduplication at the national scale. Collaborate with domain experts, biometric vendors, and legal/policy teams to ensure technological solutions are interpretable, robust, and policy compliant. Monitor system drift, adversarial threats, and fraud patterns in biometric usage across the Aadhaar ecosystem. Publish internal technical reports and participate in peer reviewed research where appropriate. Mentor and guide junior data scientists and ML engineers in best practices. What We Offer Unique opportunity to work on the largest biometric identity system in the world. Access to UIDAIs unparalleled scale of identity data and secure research environments. Competitive compensation and benefits tailored for top-tier AI talent in the public sector. A mission-driven organization with direct impact on national scale governance, security, and inclusion

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Large Language Models Good to have skills : NAMinimum 18 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an AI / ML Engineer, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve designing and implementing production-ready solutions that incorporate generative AI models, deep learning techniques, and neural networks. You will collaborate with cross-functional teams to ensure the seamless integration of AI capabilities into various applications, while also addressing challenges related to image processing and chatbot functionalities. Your role will require a balance of technical expertise and innovative thinking to drive the successful deployment of AI solutions in a cloud or on-premises environment. Roles & Responsibilities:- Expected to be a Subject Matter Expert with deep knowledge and experience.- Should have influencing and advisory skills.- Engage with multiple teams and responsible for team decisions.- Expected to provide solutions to problems that apply across multiple teams, and provide solutions to business area problems.- Facilitate knowledge sharing sessions to enhance team capabilities and foster a culture of continuous learning.- Analyze and evaluate existing systems to identify areas for improvement and optimization. Professional & Technical Skills: - Must To Have Skills: Proficiency in Large Language Models.- Strong understanding of deep learning frameworks such as TensorFlow or PyTorch.- Experience with cloud platforms like AWS, Azure, or Google Cloud for deploying AI solutions.- Familiarity with natural language processing techniques and tools.- Ability to design and implement scalable AI applications that meet business needs. Additional Information:- The candidate should have minimum 18 years of experience in Large Language Models.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Dear Candidate, We are hiring a Computer Vision Engineer to develop AI-driven solutions for image recognition, object detection, and video analysis. The role requires expertise in deep learning, computer vision algorithms, and real-time processing techniques. Key Responsibilities: Develop and optimize computer vision models using OpenCV, TensorFlow, and PyTorch. Implement object detection, segmentation, and facial recognition algorithms. Process and analyze large-scale image and video datasets. Optimize deep learning models for real-time inference on edge devices. Collaborate with AI and software teams to integrate vision solutions into applications. Required Skills & Qualifications: Computer Vision Frameworks: OpenCV, DLIB, MediaPipe Deep Learning: TensorFlow, PyTorch, Keras Algorithms: CNNs, YOLO, Faster R-CNN, Mask R-CNN Programming: Python, C++, CUDA Edge AI: TensorRT, OpenVINO, NVIDIA Jetson Experience with autonomous systems, OCR, and SLAM is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Reddy Delivery Manager Integra Technologies

Dear Candidate, We are hiring a Machine Learning Engineer to develop and deploy AI models for real-world applications. The role requires expertise in data science, model training, and cloud-based ML solutions. Key Responsibilities: Build and deploy ML models using TensorFlow, PyTorch, or Scikit-learn. Optimize models for performance and scalability. Develop data pipelines and feature engineering processes. Deploy ML solutions using AWS SageMaker, Azure ML, or Google Vertex AI. Collaborate with data scientists and software engineers to integrate AI into products. Required Skills & Qualifications: Machine Learning: TensorFlow, PyTorch, Scikit-learn Programming: Python, R Cloud ML: AWS SageMaker, Azure ML, Google Vertex AI Experience in NLP, Computer Vision, or Time Series Analysis is a plus. Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Srinivasa Reddy Kandi Delivery Manager Integra Technologies