130 Autoencoders Jobs

Area(s) of responsibility About Birlasoft Birlasoft, a powerhouse where domain expertise, enterprise solutions, and digital technologies converge to redefine business processes. We take pride in our consultative and design thinking approach, driving societal progress by enabling our customers to run businesses with unmatched efficiency and innovation. As part of the CKA Birla Group, a multibillion-dollar enterprise, we boast a 12,500+ professional team committed to upholding the Group's 162-year legacy. Our core values prioritize Diversity, Equity, and Inclusion (DEI) initiatives, along with Corporate Sustainable Responsibility (CSR) activities, demonstrating our dedication to building inclusive and sustainable communities. Join us in shaping a future where technology seamlessly aligns with purpose. About the Job – Our project is hiring a skilled Datacience Candidate who has good hands on experience on Agentic AI frameworks Job Title - DataScience Location: Noida Educational Background: Bachelor’s degree in computer science, Information Technology, or related field. Mode of Work- Hybrid Experience Required - 8+ years Key Responsibilities Must have 10+ years of experience working in Data science, Machine learning and especially NLP technologies. Solid understanding of Model development, model serving, training/re-training techniques in a data sparse environment. Must have experience with Agentic AI frameworks – LangGraph, LlamaIndex, MCP etc. Expert in using paid (OpenAI on Azure) and open source LLMs Strong understanding of Agents development. Experience with Python programming language in a must. Ability to develop Python code as needed and train the Developers based on business needs. Experience with AWS / Azure ecosystem is a must. Preferable candidate should possess Pharma R&D background Strong understanding of cloud native application development in AWS / Azure. Able to apply deep learning and generative modeling techniques to develop LLM solutions in the field of Artificial Intelligence. Utilize your extensive knowledge and expertise in machine learning (ML) with a focus on generative models, cluding but not limited to generative adversarial networks (GANs), variational autoencoders (VAEs), and transformer-based architectures. Very good understanding of Prompt engineering techniques in developing Instruction based LLMs. Must be able to design, and implement state-of-the-art generative models for natural language processing (NLP) tasks such as text generation, text completion, language translation, and document summarization. Work with SAs and collaborate with cross-functional teams to identify business requirements and deliver solutions that meet the customer needs. Passionate to learn and stay updated with the latest advancements in generative AI and LLM. Nice to have -contributions to the research community through publications, presentations, and participation in relevant conferences or workshops. Evaluate and preprocess large-scale datasets, ensuring data quality and integrity, and develop data pipelines for training and evaluation of generative models. Ability to articulate to business stakeholders on the hallucination effects and various model behavioral analysis techniques followed. Exposure to developing Guardrails for LLMs both with open source and cloud native models. Collaborate with software engineers to deploy and optimize generative models in production environments, considering factors such as scalability, efficiency, and real-time performance. Nice to have- provide guidance to junior data scientists, sharing expertise and knowledge in generative AI and LLM, and contribute to the overall growth and success of the data science team. Expert in RDBMS database Experience on Marklogic / No SQL database Experience on Elastic search

Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

Comcast brings together the best in media and technology. We drive innovation to create the world's best entertainment and online experiences. As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines. We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring cutting-edge products and services to life for millions of customers every day. If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at Comcast. Job Summary Responsible for developing and deploying machine learning algorithms. Evaluates accuracy and functionality of machine learning algorithms. Translates application requirements into machine learning problem statements. Analyzes and evaluates solutions both internally generated as well as third party supplied. Develops novel ways to use machine learning to solve problems and discover new products. Has in-depth experience, knowledge and skills in own discipline. Usually determines own work priorities. Acts as resource for colleagues with less experience. Job Description About the Role: We are seeking an experienced Data Scientist to join our growing Operational Intelligence team. You will play a key role in building intelligent systems that help reduce alert noise, detect anomalies, correlate events, and proactively surface operational insights across our large-scale streaming infrastructure. You’ll work at the intersection of machine learning, observability, and IT operations, collaborating closely with Platform Engineers, SREs, Incident Managers, Operators and Developers to integrate smart detection and decision logic directly into our operational workflows. This role offers a unique opportunity to push the boundaries of AI/ML in large-scale operations. We welcome curious minds who want to stay ahead of the curve, bring innovative ideas to life, and improve the reliability of streaming infrastructure that powers millions of users globally. What You’ll Do Design and tune machine learning models for event correlation, anomaly detection, alert scoring, and root cause inference Engineer features to enrich alerts using service relationships, business context, change history, and topological data Apply NLP and ML techniques to classify and structure logs and unstructured alert messages Develop and maintain real-time and batch data pipelines to process alerts, metrics, traces, and logs Use Python, SQL, and time-series query languages (e.g., PromQL) to manipulate and analyze operational data Collaborate with engineering teams to deploy models via API integrations, automate workflows, and ensure production readiness Contribute to the development of self-healing automation, diagnostics, and ML-powered decision triggers Design and validate entropy-based prioritization models to reduce alert fatigue and elevate critical signals Conduct A/B testing, offline validation, and live performance monitoring of ML models Build and share clear dashboards, visualizations, and reporting views to support SREs, engineers and leadership Participate in incident postmortems, providing ML-driven insights and recommendations for platform improvements Collaborate on the design of hybrid ML + rule-based systems to supportnamic correlation and intelligent alert grouping Lead and support innovation efforts including POCs, POVs, and explorationemerging AI/ML tools and strategies Demonstrate a proactive, solution-oriented mindset with the ability to navigate ambiguity and learn quickly Participate in on-call rotations and provide operational support as needed Qualifications Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field 5+ years of experience building and deploying ML solutions in production environments 2+ years working with AIOps, observability, or real-time operations data Strong coding skills in Python (including pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow) Experience working with SQL, time-series query languages (e.g., PromQL), and data transformation in pandas or Spark Familiarity with LLMs, prompt engineering fundamentals, or embedding-based retrieval (e.g., sentence-transformers, vector DBs) Strong grasp of modern ML techniques including gradient boosting (XGBoost/LightGBM), autoencoders, clustering (e.g., HDBSCAN), and anomaly detection Experience managing structured + unstructured data, and building features from logs, alerts, metrics, and traces Familiarity with real-time event processing using tools like Kafka, Kinesis, or Flink Strong understanding of model evaluation techniques including precision/recall trade-offs, ROC, AUC, calibration Comfortable working with relational (PostgreSQL), NoSQL (MongoDB), and time-series (InfluxDB, Prometheus) databases Ability to collaborate effectively with SREs, platform teams, and participate in Agile/DevOps workflows Clear written and verbal communication skills to present findings to technical and non-technical stakeholders Comfortable working across Git, Confluence, JIRA, & collaborative agile environments Nice To Have Experience building or contributing to the AIOps platform (e.g., Moogsoft, BigPanda, Datadog, Aisera, Dynatrace, BMC etc.) Experience working in streaming media, OTT platforms, or large-scale consumer services Exposure to Infrastructure as Code (Terraform, Pulumi) and modern cloud-native tooling Working experience with Conviva, Touchstream, Harmonic, New Relic, Prometheus, & event- based alerting tools Hands-on experience with LLMs in operational contexts (e.g., classification of alert text, log summarization, retrieval-augmented generation) Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings-based search for observability data Experience using MLflow, SageMaker, or Airflow for ML workflow orchestration Knowledge of LangChain, Haystack, RAG pipelines, or prompt templating libraries Exposure to MLOps practices (e.g., model monitoring, drift detection, explainability tools like SHAP or LIME) Experience with containerized model deployment using Docker or Kubernetes Use of JAX, Hugging Face Transformers, or LLaMA/Claude/Command-R models in experimentation Experience designing APIs in Python or Go to expose models as services Cloud proficiency in AWS/GCP, especially for distributed training, storage, or batch inferencing Contributions to open-source ML or DevOps communities, or participation in AIOps research/benchmarking efforts. Certifications in cloud architecture, ML engineering, or data science specializations, confluence pages, white papers, presentations, test results, technical manuals, formal recommendations and reports. Contributes to the company by creating patents, Application Programming Interfaces (APIs). Comcast is proud to be an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law. Base pay is one part of the Total Rewards that Comcast provides to compensate and recognize employees for their work. Most sales positions are eligible for a Commission under the terms of an applicable plan, while most non-sales positions are eligible for a Bonus. Additionally, Comcast provides best-in-class Benefits to eligible employees. We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That’s why we provide an array of options, expert guidance and always-on tools, that are personalized to meet the needs of your reality – to help support you physically, financially and emotionally through the big milestones and in your everyday life. Please visit the compensation and benefits summary on our careers site for more details. Education Bachelor's Degree While possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience. Relevant Work Experience 5-7 Years

Senior Manager EXL/SM/1447183 Healthcare AnalyticsNoida Posted On 09 Sep 2025 End Date 24 Oct 2025 Required Experience 11 - 20 Years Basic Section Number Of Positions 1 Band C2 Band Name Senior Manager Cost Code 8280102 Campus/Non Campus NON CAMPUS Employment Type Permanent Requisition Type New Max CTC 2000000.0000 - 3000000.0000 Complexity Level Not Applicable Work Type Hybrid – Working Partly From Home And Partly From Office Organisational Group Analytics Sub Group Healthcare Organization Healthcare Analytics LOB Healthcare D&A SBU Healthcare Analytics Country India City Noida Center Noida-SEZ BPO Solutions_Incubation Site Skills Skill ARTIFICIAL INTELLIGENCE MACHINE LEARNING ML FRAMEWORKS, PYTORCH PROMPT GENAPP Minimum Qualification MASTER OF TECHNOLOGY(MTECH) BTECH MCA MBA/PGPM Certification No data available Job Description Roles and Responsibilities: Experience in implementation of ML/AI solutions for enterprise level on Azure/AWS cloud Communicate effectively with clients on brainstorming the solutions Conduct research and development majorly on AI/ML implementations Implement RAG architecture for confidential data use case Apply deep learning techniques and machine learning experience Fine tune LLM for optimal performance Develop and implement generative AI models using state-of-the-art techniques and frameworks Collaborate with cross-functional teams to understand project requirements and design solutions that address business needs Research and experiment with new AI algorithms, architectures, and tools to improve model performance and capabilities Train, evaluate, and fine-tune generative models using large datasets to achieve desired outcomes Optimize model inference and deployment pipelines for efficiency and scalability in production environments Stay updated with the latest advancements in AI research and technology and contribute to the knowledge sharing within the team Participate in code reviews, documentation, and knowledge transfer sessions to ensure high-quality deliverables and effective collaboration Good to have - experience in healthcare and life sciences to relevant projects Leverage MLOps and LLMOps experience to optimize operations Act as a hands-on leader with GenAI and Machine Learning experience Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or related field 7+ years of experience in implementing ML/AI solutions for enterprise level on Azure/AWS cloud Strong programming skills in languages such as Python, with experience in data science Proficiency in generative AI techniques, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and related architectures Good understanding of machine learning concepts, algorithms, and methodologies Experience with data preprocessing, model training, and evaluation using large-scale datasets Excellent problem-solving skills and the ability to work independently as well as part of a team Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders Experience in healthcare and life sciences is a plus Familiarity with MLOps, AiOps, and llmops is beneficial Good to have certifications in AI/ML or related fields Workflow Workflow Type L&S-DA-Consulting

Mars Data Hiring fulltime Data Scientist-medical imaging positions in Bengaluru location Skills: Deep Learning, medical imaging, foundation models (e.g., vision transformers, multimodal models like CLIP, BioGPT, MedSAM, AI/ML algorithms for image analysis, segmentation, classification, anomaly detection, and generative tasks in Magnetic Resonance Imaging (MRI), ML pipelines, model interpretability tools, TensorFlow, PyTorch, DICOM, NIfTI, MONAI, SimpleITK, ITK-SNAP, Dice, IoU, AUC, HIPAA, FDA, MDR, PACS/RIS systems, HL7/DICOM standards, TensorRT, ONNX, OpenVINO). Job location: Bengaluru/Hybrid Shift: IST Job Type: Fulltime Experience : 5+ years Notice Period: Immediate to 15 Days We are seeking an experienced and passionate Data Scientist with deep expertise in deep learning , medical imaging , and hands-on experience with foundation models . This is a technical contributor role where you will work at the intersection of healthcare and artificial intelligence, building innovative AI solutions that transform medical diagnostics, workflows, and patient outcomes. You will be instrumental in designing and developing cutting-edge AI/ML algorithms for image analysis, segmentation, classification, anomaly detection, and generative tasks in Magnetic Resonance Imaging (MRI). Key Responsibilities: · Lead end-to-end development of deep learning models for medical imaging tasks – _from data curation and preprocessing to model training, evaluation, and deployment. · Explore and fine-tune foundation models (e.g., vision transformers, multimodal models like CLIP, BioGPT, MedSAM) for use in diagnostic and clinical imaging applications. · Drive research and prototyping of novel architectures for image segmentation, detection, and generation (e.g., UNet variants, GANs, autoencoders, diffusion models). · Collaborate cross-functionally with radiologists, product managers, software engineers, and regulatory teams to ensure clinical relevance, robustness, and compliance. · Contribute to the development of scalable ML pipelines, model interpretability tools, and performance monitoring systems. · Publish findings in peer-reviewed journals or conferences and represent the company at scientific and industry forums. · Mentor junior data scientists and guide the team on best practices in model development, validation, and documentation. Required Qualifications: PhD or master Degree in computer science or Biomedical Engineering, Applied Mathematics, or a related field. · 5+ years of experience in data science or machine learning, with at least 3 years focused on medical imaging. · Strong experience in deep learning frameworks (TensorFlow, PyTorch) and model architectures for computer vision. · Practical exposure to foundation models , including prompt engineering, fine-tuning, and domain adaptation. · Proven ability to work with 2D/3D imaging datasets (DICOM, NIfTI), and medical imaging toolkits (e.g., MONAI, SimpleITK, ITK-SNAP). · Expertise in evaluation metrics specific to medical imaging (Dice, IoU, AUC, etc.) and experience working with imbalanced datasets. · Solid understanding of healthcare data compliance (HIPAA, FDA, MDR) and medical device AI/ML lifecycle. · Excellent problem-solving, communication, and leadership skills. Preferred Qualifications: · Publications or patents in AI for healthcare or medical imaging domains. · Experience with PACS/RIS systems, HL7/DICOM standards, and clinical workflows. · Familiarity with LLMs or multimodal generative models in a clinical context. · Exposure to MLOps, model deployment, and on-device inference optimization (e.g., TensorRT, ONNX, OpenVINO). share your resume to hr@marsdata.in

Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

C5i caters to some of the worlds largest enterprises, including many Fortune 500 companies. The companys clients span Technology, Media, and Telecom (TMT), Pharma & Lifesciences, CPG, Retail, Banking, and other sectors. C5i has been recognized by leading industry analysts like Gartner and Forrester for its Analytics and AI capabilities and proprietary AI-based platforms. We are seeking a highly skilled Data Scientist with a passion for AI, machine learning, and deep learning to join our dynamic team. The ideal candidate will have experience in generative models, LLMs, and advanced AI techniques, and will contribute to solving complex business Title : Data Scientist (Generative AI : Bengaluru, Gurugram, Mumbai, : 4+years Of experience in machine learning, deep learning, or Al research, With a focus on generative models. Experience With generative models such as GANS (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models (e.g., GPT-3/4, BERT, DALL.E). Understanding of model fine-tuning, transfer learning, and prompt engineering in the context Of large language models (LLMS). Knowledge of reinforcement learning (RL) and other advanced machine learning techniques applied to generative tasks. Strong programming skills in python and familiarity With relevant libraries and frameworks. Proven experience in document detail extraction and feature engineering. Proficiency in data processing and manipulation techniques. Hands-on experience in building data applications using Streamlit or similar tools. Advanced knowledge in prompt engineering, chain of thought processes, and Al agents. Excellent problem-solving skills and the ability to work effectively in a collaborative environment. Strong communication skills to convey complex technical concepts to non-technical stakeholders. (ref:hirist.tech)

About C5i C5i is a pure-play AI & Analytics provider that combines the power of human perspective with AI technology to deliver trustworthy intelligence. The company drives value through a comprehensive solution set, integrating multifunctional teams that have technical and business domain expertise with a robust suite of products, solutions, and accelerators tailored for various horizontal and industry-specific use cases. At the core, C5is focus is to deliver business impact at speed and scale by driving adoption of AI-assisted decision-making. C5i caters to some of the worlds largest enterprises, including many Fortune 500 companies. The companys clients span Technology, Media, and Telecom (TMT), Pharma & Lifesciences, CPG, Retail, Banking, and other sectors. C5i has been recognized by leading industry analysts like Gartner and Forrester for its Analytics and AI capabilities and proprietary AI-based platforms. Required Skills 3+years of experience in machine learning, deep learning, or Al research, With a focus on generative models. Experience With generative models such as GANS (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models (e.g., GPT-3/4, BERT, DALL.E) RAG and Prompt Engineering. Understanding of model fine-tuning, transfer learning, and prompt engineering in the context Of large language models (LLMS). Strong programming skills in python and familiarity with relevant libraries and frameworks. Hands-on experience in building data applications using Streamlit or similar tools. Deep understanding of transformer architecture, including multi-head attention, layer normalization, and residual connections. Proficiency with Hugging Face Transformers, PyTorch or TensorFlow. Experience in training and deploying LLMs for tasks like text generation, summarization, or translation. Familiarity with AdamW, learning rate warm-up, and optimization strategies. Exposure to advanced transformer variants (e.g., Transformer-XL, Longformer, BigBird, LoRA). Solid debugging and performance tuning skills. Good-to-Have Experience with Docker, Kubernetes, and MLOps. Knowledge of CI/CD pipelines and model deployment best practices. (ref:hirist.tech)

Job description : ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

About Us At NexusLink Services, we are passionate about building intelligent, scalable solutions that drive real-world impact. As we expand our AI/ML capabilities, were looking for a Generative AI-focused Data Scientist to join our innovative and rapidly growing team. Role Overview We are seeking an experienced Data Scientist with 4- 6 years of hands-on experience and deep expertise in Generative AI to design and implement cutting-edge models that address real business challenges. You will work with LLMs, GANs, RAG frameworks, and transformer-based architectures to build scalable, production-ready solutions across industries. Key Responsibilities Design, develop, and fine-tune Generative AI models (LLMs, GANs, Diffusion models, etc. Work on RAG (Retrieval-Augmented Generation) and transformer-based architectures. Customize and fine-tune LLMs for domain-specific use cases. Build and manage robust ML pipelines for training, evaluation, and deployment. Collaborate with engineering teams to integrate models into real-world applications. Stay updated with the latest GenAI research, tools, and trends. Analyze model outputs, monitor performance, and ensure responsible AI use. Required Skills 4- 6 years of experience in data science or machine learning roles. Strong Python skills with experience in ML/DL libraries : TensorFlow, PyTorch, HuggingFace Transformers. Deep understanding of LLMs, GANs, RAG, Autoencoders, etc. Experience with LoRA, PEFT, or similar fine-tuning techniques. Familiarity with Vector Databases (FAISS, Pinecone) and embeddings. Expertise in data preprocessing, synthetic data generation. Solid knowledge of NLP, prompt engineering, and language model safety. Hands-on experience with model deployment, APIs, and cloud platforms (AWS/GCP/Azure). Nice To Have Experience with Chatbots, Conversational AI, or AI Assistants. Familiarity with LangChain, LLMOps, or serverless model deployment. Background in MLOps, Docker/Kubernetes, and CI/CD pipelines. Exposure to OpenAI, Anthropic, Google Gemini, or Meta LLaMA. (ref:hirist.tech)

T Job description We are seeking a highly skilled Data Scientist with a passion for AI, machine learning, and deep learning to join our dynamic team. The ideal candidate will have experience in generative models, LLMs, and advanced AI techniques, and will contribute to solving complex business challenges. Job Title: Data Scientist (Generative AI LLMs) Location: Bengaluru, Gurugram, Mumbai, Coimbatore 4+years Of experience in machine learning, deep learning, or Al research, With a focus on generative models. Experience With generative models such as GANS (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models (e.g., GPT-3/4, BERT, DALL.E). Understanding of model fine-tuning, transfer learning, and prompt engineering in the context Of large language models (LLMS). Knowledge of reinforcement learning (RL) and other advanced machine learning techniques applied to generative tasks. Strong programming skills in python and familiarity With relevant libraries and frameworks. Proven experience in document detail extraction and feature engineering. Proficiency in data processing and manipulation techniques. Hands-on experience in building data applications using Streamlit or similar tools. Advanced knowledge in prompt engineering, chain of thought processes, and Al agents. Excellent problem-solving skills and the ability to work effectively in a collaborative environment. Strong communication skills to convey complex technical concepts to non-technical stakeholders.

· Proficiency in designing and building chatbot systems, including knowledge of natural language processing (NLP) techniques, dialog management, and creating conversational flows to deliver engaging user experiences. · Strong understanding of various machine learning algorithms, including supervised and unsupervised learning, as well as experience in training, evaluating, and deploying machine learning models for real-world applications. · Proficiency in programming languages commonly used in AI and machine learning projects, such as Python, Java, or C++. Ability to write clean, efficient, and maintainable code. · Knowledge of generative AI models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. Ability to leverage these models for tasks such as text generation, image synthesis, or data augmentation. · Proficiency in data preprocessing, cleaning, and feature engineering techniques to prepare datasets for training and analysis. Understanding of data augmentation strategies to enhance model performance. · Familiarity with popular AI frameworks like TensorFlow, PyTorch, or Keras. Experience in using these frameworks to implement and optimize AI models. · Familiarity with version control systems like Git to manage codebase changes, collaborate with other developers, and maintain a clean project history. · Basic knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services for model deployment, scalability, and management. · Experience with performance optimization and debugging techniques. · Experience in deploying AI models using Flask or similar frameworks on the web, including integration, optimization, and issue resolution. Job Type: Full-time Pay: ₹900,000.00 - ₹1,200,000.00 per year Ability to commute/relocate: Noida H.O, Noida, Uttar Pradesh: Reliably commute or planning to relocate before starting work (Required) Education: Master's (Preferred) Experience: total work: 4 years (Required) Work Location: In person

AI/ML Engineer (UAV Perception) Position: AI/ML Engineer (3–4 roles) Location: Aluva / Kochi, India (with field testing at UAV ranges) Department: UAV AI Division, Canary Digital.ai Role Overview As an AI/ML Engineer (UAV Perception) , you will design, train, and deploy computer vision and sensor fusion models for Canary Digital’s UAV platforms. Your work will focus on object detection, anomaly detection, EO/IR fusion, and real-time inference on Jetson-class edge devices , enabling UAVs to autonomously detect threats, intrusions, and unusual occurrences. You will collaborate with UAV Systems Engineers and RF/Comms specialists to deliver an end-to-end AI-powered UAV solution for defense and security. Key Responsibilities Develop and deploy real-time computer vision models (object/person/vehicle detection, tracking, re-ID) on Jetson devices. Build change detection and anomaly detection pipelines for perimeter security and patrol missions. Integrate EO (RGB) + IR (thermal) sensor fusion models for day/night operations. Optimize models for low-latency inference using TensorRT, DeepStream, CUDA. Create synthetic datasets for rare threat scenarios (weapons, intrusions, tampering). Collect, annotate, and retrain models from field UAV test data . Collaborate with RF engineers for friend/foe beacon + CV hybrid detection . Implement MLOps workflows : versioned datasets, model deployment pipelines, performance monitoring. Support Weather Guard AI integration for weather-aware perception tuning. Required Skills & Experience 2–6 years of experience in AI/ML or Computer Vision engineering . Strong background in Deep Learning frameworks (PyTorch, TensorFlow). Proficiency in object detection/tracking architectures (YOLOv8, Detectron2, EfficientDet, SORT/DeepSORT). Familiarity with anomaly detection methods (autoencoders, clustering, unsupervised ML). Hands-on with NVIDIA Jetson platform (TensorRT, DeepStream, CUDA). Strong Python/C++ coding skills. Experience with dataset annotation, augmentation, and synthetic data generation . Preferred Background Prior projects in autonomous systems, robotics, or defense AI . Experience with AirSim/Gazebo simulation data pipelines . Knowledge of multi-sensor fusion (EO/IR, lidar, radar). Familiarity with real-time constraints in embedded AI systems. What We Offer Work on mission-critical UAV AI perception systems with national impact. Collaborate with UAV engineers, RF specialists, and defense partners. Access to Jetson dev kits, EO/IR sensors, UAV test flights . Competitive salary + performance-based incentives

Role description STL Digital is a global IT Services and Consulting company that enables enterprises to experience the future of digital transformation. We provide end to end services across product engineering, software, cloud, data and analytics, enterprise application services, and cyber-security. Purpose - We Engineer Experiences that create value. We blend the agility of a startup with the stability of an established enterprise. We're passionate about innovation. Our culture is built on 4 core values: 1. Respect for Individuals: We value every team member's unique perspective and contributions. 2. Hunger to Learn: We encourage continuous growth and development. 3. Promises Delivered: We are committed to delivering on our commitments. 4. Keep it Simple: We strive for clarity and efficiency in everything we do. We're looking for talented individuals to join us on this exciting journey, working with our 25+ Global Customers. Let's build the future of tech together. Job Title : Data Scientist Work Location : Udaipur Experience : 3-5 Yrs. Job Mode : Work from office Responsibilities: Role Overview We are seeking a Data Scientist to lead AI/ML initiatives and deliver end-to-end analytics solutions on Microsoft Azure. The role spans data engineering, model development, deployment, monitoring, and governance—combining Python, SQL, and machine learning expertise with practical cloud deployment skills to solve business challenges at scale. This position offers exposure to predictive & prescriptive analytics, computer vision, and Generative AI, along with hands-on experience in MLOps and cloud orchestration, enabling candidates to drive digital transformation while accelerating their professional growth at the intersection of data, cloud, and business impact. Key Responsibilities 1. Data Acquisition & Understanding Collaborate with stakeholders to identify business problems suitable for AI/ML solutions. Gather structured and unstructured data from multiple sources (PI historian, SQL databases, APIs, IoT systems, cloud storage). Perform Exploratory Data Analysis (EDA) to understand data distribution, anomalies, and patterns. 2. Data Cleaning & Feature Engineering Preprocess raw data to handle missing values, outliers, and inconsistencies. Perform feature extraction, transformation, and selection to enhance model performance. Apply dimensionality reduction and encoding techniques where necessary. 3. Model Development & Evaluation Build predictive and prescriptive models using supervised, unsupervised, and reinforcement learning techniques. Implement regression, classification, clustering, time-series forecasting, and deep learning algorithms. Evaluate models using appropriate metrics (accuracy, RMSE, R2-score, precision, recall, confusion matrix) Perform hyperparameter tuning and model optimization. 4. Deployment & Cloud Management Deploy models on MS Azure, ensuring scalability, availability, and security. Maintain and monitor performance of deployed models, retraining as needed. Optimize cloud resource usage and manage pipelines using Azure Machine Learning and related Services. 5. Reporting & Visualization Communicate model insights and recommendations to business stakeholders. Develop dashboards and reports to track model performance and business impact. Ensure reproducibility, documentation, and version control of all models and code. 6. Administration & Governance Ensure proper administration, housekeeping, and lifecycle management of deployed AI/ML models and Azure resources. Support version control, access management, and cost optimization of ML solutions in the cloud with IT Team. Establish monitoring practices to ensure compliance, security, and sustainability of digital assets. Leverage emerging AI/ML technologies (Generative AI, NLP, Computer Vision) to drive innovation and business optimization. Qualification Required Bachelor’s / Master’s degree preferably in Engineering, Computer Science, Statistics, Data Science, or related disciplines. Candidates from any other discipline with strong experience in AI/ML, data analytics, and cloud deployment (Python + Azure) are encouraged to apply. Additional certifications such as Microsoft Certified: Azure Data Scientist Associate or Azure AI Engineer Associate will be an added advantage. Technical Skills & Tools Programming Languages: Python, SQL Tools & Platforms: Jupyter Notebook (Anaconda), MS Azure, SSMS, Power BI (Optional) Python Libraries & Frameworks: Data Processing & Visualization: pandas, numpy, matplotlib, seaborn, plotly Supervised Learning: scikit-learn, XGBoost Unsupervised Learning: scikit-learn, hdbscan, umap-learn Deep Learning / Computer Vision: TensorFlow, Keras, OpenCV, Detectron2 / YOLO Natural Language Processing / Generative AI (Optional): transformers (GPT, LLaMA), spaCy Algorithms / Techniques: Supervised Learning: Regression (Multi Linear Regression, Logistic Regression), Tree-based Models (Decision Trees, Random Forest), Gradient Boosting (XGBoost) Unsupervised Learning: Clustering (K-Means, Hierarchical Clustering), Dimensionality Reduction (Principal Component Analysis - PCA) Deep Learning: Convolutional Neural Networks - CNNs (for image processing & computer vision), Recurrent Neural Networks - RNNs (LSTMs – for sequential data & time series), Autoencoders (for anomaly detection, dimensionality reduction) Generative AI / NLP (Optional): Fundamentals of Transformer Models and Large Language Models (GPT, LLaMA, Claude, Gemini) Cloud & Deployment Skills (MS Azure): Azure Machine Learning (AML): End-to-end ML lifecycle (training, deployment, MLOps). Azure Blob Storage / Data Lake Storage: Raw data storage, feature store, model artifacts. Azure Functions: Serverless compute for lightweight inference or automation tasks. Azure App Service / Azure API Management: Hosting ML models Azure Monitor & Application Insights: Tracking model performance, drift detection, logs, s. Azure Databricks (Optional): Advanced data engineering, large-scale ML model training, Spark-based analytics. Azure Data Factory (Optional): Data ingestion, ETL pipelines, orchestration. Azure Cognitive Services (Optional): Pre-built AI for computer vision, NLP, speech Skills About Sterlite Technologies Limited About STL - STL is a leading global optical and digital solutions company providing advanced offerings to build 5G, Rural, FTTx, Enterprise and Data Centre networks. About STL Digital - STL Digital, a wholly owned subsidiary of STL, is a global IT services and consulting company dedicated to delivering exceptional digital transformation experiences for enterprises with a comprehensive portfolio of services, including product engineering, cloud and cyber security, data and AI, and enterprise SaaS.

Role description STL Digital is a global IT Services and Consulting company that enables enterprises to experience the future of digital transformation. We provide end to end services across product engineering, software, cloud, data and analytics, enterprise application services, and cyber-security. Purpose - We Engineer Experiences that create value. We blend the agility of a startup with the stability of an established enterprise. We're passionate about innovation. Our culture is built on 4 core values: 1. Respect for Individuals: We value every team member's unique perspective and contributions. 2. Hunger to Learn: We encourage continuous growth and development. 3. Promises Delivered: We are committed to delivering on our commitments. 4. Keep it Simple: We strive for clarity and efficiency in everything we do. We're looking for talented individuals to join us on this exciting journey, working with our 25+ Global Customers. Let's build the future of tech together. Job Title : Data Scientist Work Location : Udaipur Experience : 3-5 Yrs. Job Mode : Work from office Responsibilities: Role Overview We are seeking a Data Scientist to lead AI/ML initiatives and deliver end-to-end analytics solutions on Microsoft Azure. The role spans data engineering, model development, deployment, monitoring, and governance—combining Python, SQL, and machine learning expertise with practical cloud deployment skills to solve business challenges at scale. This position offers exposure to predictive & prescriptive analytics, computer vision, and Generative AI, along with hands-on experience in MLOps and cloud orchestration, enabling candidates to drive digital transformation while accelerating their professional growth at the intersection of data, cloud, and business impact. Key Responsibilities 1. Data Acquisition & Understanding Collaborate with stakeholders to identify business problems suitable for AI/ML solutions. Gather structured and unstructured data from multiple sources (PI historian, SQL databases, APIs, IoT systems, cloud storage). Perform Exploratory Data Analysis (EDA) to understand data distribution, anomalies, and patterns. 2. Data Cleaning & Feature Engineering Preprocess raw data to handle missing values, outliers, and inconsistencies. Perform feature extraction, transformation, and selection to enhance model performance. Apply dimensionality reduction and encoding techniques where necessary. 3. Model Development & Evaluation Build predictive and prescriptive models using supervised, unsupervised, and reinforcement learning techniques. Implement regression, classification, clustering, time-series forecasting, and deep learning algorithms. Evaluate models using appropriate metrics (accuracy, RMSE, R2-score, precision, recall, confusion matrix) Perform hyperparameter tuning and model optimization. 4. Deployment & Cloud Management Deploy models on MS Azure, ensuring scalability, availability, and security. Maintain and monitor performance of deployed models, retraining as needed. Optimize cloud resource usage and manage pipelines using Azure Machine Learning and related Services. 5. Reporting & Visualization Communicate model insights and recommendations to business stakeholders. Develop dashboards and reports to track model performance and business impact. Ensure reproducibility, documentation, and version control of all models and code. 6. Administration & Governance Ensure proper administration, housekeeping, and lifecycle management of deployed AI/ML models and Azure resources. Support version control, access management, and cost optimization of ML solutions in the cloud with IT Team. Establish monitoring practices to ensure compliance, security, and sustainability of digital assets. Leverage emerging AI/ML technologies (Generative AI, NLP, Computer Vision) to drive innovation and business optimization. Qualification Required Bachelor’s / Master’s degree preferably in Engineering, Computer Science, Statistics, Data Science, or related disciplines. Candidates from any other discipline with strong experience in AI/ML, data analytics, and cloud deployment (Python + Azure) are encouraged to apply. Additional certifications such as Microsoft Certified: Azure Data Scientist Associate or Azure AI Engineer Associate will be an added advantage. Technical Skills & Tools Programming Languages: Python, SQL Tools & Platforms: Jupyter Notebook (Anaconda), MS Azure, SSMS, Power BI (Optional) Python Libraries & Frameworks: Data Processing & Visualization: pandas, numpy, matplotlib, seaborn, plotly Supervised Learning: scikit-learn, XGBoost Unsupervised Learning: scikit-learn, hdbscan, umap-learn Deep Learning / Computer Vision: TensorFlow, Keras, OpenCV, Detectron2 / YOLO Natural Language Processing / Generative AI (Optional): transformers (GPT, LLaMA), spaCy Algorithms / Techniques: Supervised Learning: Regression (Multi Linear Regression, Logistic Regression), Tree-based Models (Decision Trees, Random Forest), Gradient Boosting (XGBoost) Unsupervised Learning: Clustering (K-Means, Hierarchical Clustering), Dimensionality Reduction (Principal Component Analysis - PCA) Deep Learning: Convolutional Neural Networks - CNNs (for image processing & computer vision), Recurrent Neural Networks - RNNs (LSTMs – for sequential data & time series), Autoencoders (for anomaly detection, dimensionality reduction) Generative AI / NLP (Optional): Fundamentals of Transformer Models and Large Language Models (GPT, LLaMA, Claude, Gemini) Cloud & Deployment Skills (MS Azure): Azure Machine Learning (AML): End-to-end ML lifecycle (training, deployment, MLOps). Azure Blob Storage / Data Lake Storage: Raw data storage, feature store, model artifacts. Azure Functions: Serverless compute for lightweight inference or automation tasks. Azure App Service / Azure API Management: Hosting ML models Azure Monitor & Application Insights: Tracking model performance, drift detection, logs, s. Azure Databricks (Optional): Advanced data engineering, large-scale ML model training, Spark-based analytics. Azure Data Factory (Optional): Data ingestion, ETL pipelines, orchestration. Azure Cognitive Services (Optional): Pre-built AI for computer vision, NLP, speech

ExcelR is seeking experienced AI and Machine Learning trainers to deliver a comprehensive AI and Machine Learning curriculum. The training program will span 40 working days, with daily classes of 5–6 hours, tentatively from August 20, 2025, to October 21, 2025. The role involves teaching theoretical concepts, guiding hands-on projects, and mentoring students on real-world AI/ML applications. Skills Required : Foundational ML: Logistic Regression, SVM, Decision Trees, Ensemble Methods (Bagging, Random Forests), Boosting (Gradient Boosting, AdaBoost, XGBoost, LightGBM), PCA, Clustering (K-means, Hierarchical, DBSCAN), Market Basket Analysis, and Recommendation Systems. Deep Learning: ANN, CNN, RNN, LSTM, GRU, Transformers, GANs, Autoencoders, Diffusion Models (Stable Diffusion), and LLMs (e.g., GPT, BERT). Data Preprocessing: Standardization, normalization, encoding, train-test split, cross-validation, regularization (Lasso, Ridge, ElasticNet), and feature engineering. Generative AI: Text-to-image/audio/video generation, chatbots, sentiment analysis, and Retrieval-Augmented Generation (RAG) with FAISS. Web & Cloud Deployment: Building and deploying RESTful APIs using Flask/FastAPI, cloud computing with AWS (EC2, S3, Lambda) and Azure (Blob, App Services), and Streamlit for project deployment. Mathematics: Calculus, vector algebra, probability. Prompt Engineering: Zero-shot, few-shot, prompt tuning, and designing effective prompts. Case Studies: Hands-on projects (e.g., Bangalore housing prices, Breast cancer classification, Sales dataset). Qualifications : Education: Bachelor’s/Master’s in Computer Science, AI, ML, or related fields. Experience: 3–5 years in Machine Learning, Deep Learning, and Full Stack AI development, with hands-on experience in: Python and libraries like scikit-learn, TensorFlow, Keras, PyTorch. Generative AI (GANs, Diffusion Models, LLMs like GPT-2, LLaMA). Web development (Flask, FastAPI) and cloud deployment (AWS EC2, Azure). Tools like Hugging Face, FAISS, LangChain, and Streamlit. Teaching Skills: Prior teaching/training experience preferred, with the ability to explain complex topics (e.g., attention mechanisms, PCA) to undergraduate students. Certifications: Relevant certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Professional ML Engineer) are a plus.

Data science internship at Sekuen LLC About Sekuen https://www.sekuen.com/blog Sekuen is an AI agency located in Dubai, offering AI solutions in several industries like regulation tech, biotech, adtech etc Some of our recent products include: Building AI agents that monitor changes in regulations for green ESG building regulations in Germany. Building a 700 classes (IAB taxonomy) video classifier with 98% accuracy. Building AI agents for live monitoring in FDA regulations in order to help meds formulation passing the new regulations exams Location Dubai, UAE Remote available Duration 3-4 months At the end of which the company proceeds to a student evaluation protocol. This position could open the door to full time later depending on the availability and at the discretion of the company executives. Starting Within 1 week Immediate preferable Compensation Select interns stipends are available Language English Arabic (optional) Working hours Full time, 40 hours per week Monday-Friday 11 am to 8 pm GST (Dubai time) What will you learn? Working with Sekuen LLC, you will get exposed to most of the following hot topics in data science Matrix multiplication, matrix inversion, Eigendecomposition, SVD SVM, Logistic regression, KNN, K-means Decision trees, Random Forests, XGBOOST Autoencoders, Transformers, attention FFT, Laplace transform GAN, generative and agentic AI NN, RNN, CNN, Reinforcement learning NLP, text cleanups, LLM generators, recommenders, publications classification Social media video marketing Prerequisites Full time availability for the full duration Should be available to accept a full time position right at the end of the training program Should be able to present some previous/current ML/AI projects Proven excellence and distinction in maths and data science applications Python, Colab are prerequisites NLP, CNN, Bitbucket/Git and version control are a plus Scientific background is desirable (Phys, Chem, Bio, Med, Pharma) Nail your interview Basic intro to NLP https://www.youtube.com/playlist?list=PLQY2H8rRoyvzDbLUZkbudP-MFQZwNmU4S Basics of machine learning algorithms https://www.youtube.com/@SerranoAcademy Basics of mathematics https://www.youtube.com/@3blue1brown Advanced machine learning for control https://www.youtube.com/@Eigensteve/ Desired but not mandatory Certified Agentic AI Professional (GSDC) AAIA (Advanced in AI Audit, ISACA) Certified AI Transformation Leader (CAITL) Artificial Intelligence Governance Professional (AIGP, IAPP) Salesforce AI Associate Cloud certifications (AWS/GCP/Azure) Professional Data Science/AI certificates Know your interviewer https://www.linkedin.com/in/samirzein/ How to apply? Write a 3-4 paragraphs email to career@sekuen.com Explain why you are the best fit for the above and attach a 1 page CV , listing mostly projects related to ML/DL you performed in the past, and your curriculum in math Subject/title of your message “Fall 2025: I have both AI coding and maths skills”

AI/ML Engineer (UAV Perception) Position: AI/ML Engineer (3–4 roles) Location: Aluva / Kochi, India (with field testing at UAV ranges) Department: UAV AI Division, Canary Digital.ai Role Overview As an AI/ML Engineer (UAV Perception) , you will design, train, and deploy computer vision and sensor fusion models for Canary Digital’s UAV platforms. Your work will focus on object detection, anomaly detection, EO/IR fusion, and real-time inference on Jetson-class edge devices , enabling UAVs to autonomously detect threats, intrusions, and unusual occurrences. You will collaborate with UAV Systems Engineers and RF/Comms specialists to deliver an end-to-end AI-powered UAV solution for defense and security. Key Responsibilities Develop and deploy real-time computer vision models (object/person/vehicle detection, tracking, re-ID) on Jetson devices. Build change detection and anomaly detection pipelines for perimeter security and patrol missions. Integrate EO (RGB) + IR (thermal) sensor fusion models for day/night operations. Optimize models for low-latency inference using TensorRT, DeepStream, CUDA. Create synthetic datasets for rare threat scenarios (weapons, intrusions, tampering). Collect, annotate, and retrain models from field UAV test data . Collaborate with RF engineers for friend/foe beacon + CV hybrid detection . Implement MLOps workflows : versioned datasets, model deployment pipelines, performance monitoring. Support Weather Guard AI integration for weather-aware perception tuning. Required Skills & Experience 2–6 years of experience in AI/ML or Computer Vision engineering . Strong background in Deep Learning frameworks (PyTorch, TensorFlow). Proficiency in object detection/tracking architectures (YOLOv8, Detectron2, EfficientDet, SORT/DeepSORT). Familiarity with anomaly detection methods (autoencoders, clustering, unsupervised ML). Hands-on with NVIDIA Jetson platform (TensorRT, DeepStream, CUDA). Strong Python/C++ coding skills. Experience with dataset annotation, augmentation, and synthetic data generation . Preferred Background Prior projects in autonomous systems, robotics, or defense AI . Experience with AirSim/Gazebo simulation data pipelines . Knowledge of multi-sensor fusion (EO/IR, lidar, radar). Familiarity with real-time constraints in embedded AI systems. What We Offer Work on mission-critical UAV AI perception systems with national impact. Collaborate with UAV engineers, RF specialists, and defense partners. Access to Jetson dev kits, EO/IR sensors, UAV test flights . Competitive salary + performance-based incentives

We are seeking a highly skilled Development Lead with expertise in Generative AI and Large Language models to join our dynamic team. As a Development Lead, you will play a key role in developing cutting-edge AI models and systems for our clients. Your primary focus will be on driving innovation and leveraging generative AI techniques to create impactful solutions. The ideal candidate will have a strong technical background and a passion for pushing the boundaries of AI technology. Job Description: Responsibilities : Develop and implement creative experiences, campaigns, apps, and digital products, leveraging generative AI technologies at their core. Successful leadership and delivery of projects involving Cloud Gen-AI Platforms and Cloud AI Services, Data Pre-processing, Cloud AI PaaS Solutions, LLMs, Base Foundation Models, Fine Tuned models, working with a variety of different LLMs and LLM APIs. Conceptualize, Design, build and develop experiences and solutions which demonstrate the minimum required functionality within tight timelines. Collaborate with creative technology leaders and cross-functional teams to test feasibility of new ideas, help refine and validate client requirements and translate them into working prototypes, and from thereon to scalable Gen-AI solutions. Research and explore emerging trends and techniques in the field of generative AI and LLMs to stay at the forefront of innovation. Research and explore new products, platforms, and frameworks in the field of generative AI on an ongoing basis and stay on top of this very dynamic, evolving field Design and optimize Gen-AI Apps for efficient data processing and model leverage. Implement LLMOps processes, and the ability to manage Gen-AI apps and models across the lifecycle from prompt management to results evaluation. Evaluate and fine-tune models to ensure high performance and accuracy. Collaborate with engineers to develop and integrate AI solutions into existing systems. Stay up-to-date with the latest advancements in the field of Gen-AI and contribute to the company's technical knowledge base. Must-Have: Strong Expertise in Python development, and the Python Dev ecosystem, including various frameworks/libraries for front-end and back-end Python dev, data processing, API integration, and AI/ML solution development. Minimum 2 years hands-on experience in working with Generative AI Applications and Solutions. Minimum 2 years hands-on experience in working with Large Language Models Solid understanding of Transformer Models and how they work. Reasonable understanding of Diffusion Models and how they work. Hands-on Experience with building production solutions using a variety of different. Experience with multiple LLMs and models - including GPT-4o, Gemini, Claude, Llama, etc. Deep Experience and Expertise in Cloud Gen-AI platforms, services, and APIs, including Azure OpenAI, AWS Bedrock, and/or GCP Vertex AI. Solid Hands-on Experience working with Enterprise RAG technologies and solutions / frameworks - including LangChain, Llama Index, etc. Solid Hands-on Experience with developing end-to-end RAG Pipelines. Solid Hands-on Experience with Agent-driven Gen-AI architectures and solutions, and working with AI Agents. Hands-on experience with Single-Agent and Multi-Agent Orchestration solutions Solid Hands-on Experience with AI and LLM Workflows Experience with LLM model registries (Hugging Face), LLM APIs, embedding models, etc. Experience with vector databases (Azure AI Search, AWS Kendra, FAISS, Milvus etc.). Experience in data preprocessing, and post-processing model / results evaluation. Hands-on Experience with Diffusion Models and AI. Art models including SDXL, DALL-E 3, Adobe Firefly, Midjourney, is highly desirable. Hands-on Experience with Image Processing and Creative Automation at scale, using AI models. Hands-on experience with image and media transformation and adaptation at scale, using AI Art and Diffusion models. Hands-on Experience with dynamic creative use cases, using AI Art and Diffusion Models. Hands-on Experience with Fine-Tuning LLM models at scale. Hands-on Experience with Fine-Tuning Diffusion models and Fine-tuning techniques such as LoRA for AI Art models as well. Hands-on Experience with AI Speech models and services, including Text-to-Speech and Speech-to-Text. Ability to lead design and development teams, for Full-Stack Gen-AI Apps and Products/Solutions, built on LLMs and Diffusion models. Ability to lead design and development for Creative Experiences and Campaigns, built on LLMs and Diffusion models. Nice-to-Have: Good Background and Foundation with Machine Learning solutions and algorithms Experience with designing, developing, and deploying production-grade machine learning solutions. Experience with Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Experience with custom ML model development and deployment Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras. Strong knowledge of machine learning algorithms and their practical applications. Experience with Cloud ML Platforms such as Azure ML Service, AWS Sage maker, and NVidia AI Foundry. Hands-on Experience with Video Generation models. Hands-on Experience with 3D Generation Models. Location: DGS India - Pune - Kharadi EON Free Zone Brand: Dentsu Creative Time Type: Full time Contract Type: Permanent

Role: Machine Learning / Computer Vision Engineer 27281 Job Description Develop advanced image processing algorithms for wafer inspection. Apply deep understanding of machine learning and computer vision, with familiarity in major deep-learning architectures such as CNN, GAN, and Transformer. Write efficient, production-grade code in Python or C++; experience with Linux is preferred. Work with major deep learning frameworks such as TensorFlow or PyTorch. Collaborate effectively in cross-functional teams with strong written and verbal communication skills. Experience with unsupervised machine learning, handling large datasets, and anomaly detection is a plus. End-to-end deployment experience of ML/DL algorithmic solutions is preferred. Minimum Qualifications Educational Background: Ph.D., Dual Degree, Master’s, or Bachelor’s in EE, CS, Mathematics, or related fields. Strong foundation in machine vision. Knowledge and practical experience in deep learning using frameworks like TensorFlow, PyTorch, or Theano. Hands-on experience with techniques such as GANs, Autoencoders, or Semantic Segmentation. Ability to translate real-world problems into mathematical models. Must-Haves Total experience: Not more than 9 years. Education/Experience: B.Tech/M.Sc. with minimum 4+ years, OR M.Tech/M.S. with minimum 3+ years, OR Ph.D. with 0 years (only from Tier-1 institutions). Candidates should have studied in Tier-1 institutes (IIT, IIIT, IISc, NIT, VIT, PSG, CEG, or Tier-1 state colleges). Experience: Minimum 4 years in Artificial Intelligence, Machine Learning, and Deep Learning. At least 2 years in Computer Vision / Image Processing. Consistent career stability (minimum 2 years in each organization). Willingness to relocate to Chennai. Skills: learning,machine learning,computer vision,deep learning,d,image processing,processing,tensorflow,pytorch,advanced

You will be responsible for researching, designing, developing, and deploying advanced predictive machine learning models in a hands-on manner. Additionally, you will be developing and implementing systematic trading strategies based on the model predictions. Your role will involve reading financial literature and academic papers to identify market inefficiencies and gain inspiration. You will need to form hypotheses about market patterns and dependencies and rigorously test them. It is essential to think creatively, innovate, and solve complex problems in this role. You will also be expected to learn about financial markets and instruments to predict their future performance, contributing to the development of best practices within the firm. To excel in this position, you should have an eagerness to learn about financial markets and ways to predict the performance of businesses and their stock prices. A minimum of 5 years of experience in analyzing large amounts of data using Python or R is required. Extensive experience in training and implementing models with Scikit-learn, Pytorch, and/or Tensorflow is essential. You should have a solid understanding of linear algebra, time series analysis, data mining, numerical methods, and statistical tools, including PCA and regression. A proven track record of dedication and perseverance in solving complex problems is highly valued. Excellent English communication skills, both written and oral, are a must. Soft skills are also crucial for this role. You should possess excellent communication skills, both written and oral, along with self-awareness, intellectual curiosity, and a team-player mentality. Being a self-starter, enthusiastic, and positive thinker will contribute to your success in this position. In addition to the aforementioned requirements, it would be advantageous to have a degree in a technical or quantitative discipline like statistics, mathematics, physics, electrical engineering, or computer science. Exposure to packages such as pandas, NumPy, stats models, sklearn, scipy, matplotlib, and TensorFlow is beneficial. C++ experience is considered an advantage. An interest or experience in machine learning techniques, time series analysis, and econometrics is preferred. Experience in Deep Learning, including DNN, CNN, RNN/LSTM, GAN, or other autoencoders, is a plus. This opportunity is with Nirvana Solutions and was posted by Aayushi K.,

About Firstsource Firstsource Solutions Limited, an RP-Sanjiv Goenka Group company (NSE: FSL, BSE: 532809, Reuters: FISO.BO, Bloomberg: FSOL:IN), is a specialized global business process services partner, providing transformational solutions and services spanning the customer lifecycle across Healthcare, Banking and Financial Services, Communications, Media and Technology, Retail, and other diverse industries. With an established presence in the US, the UK, India, Mexico, Australia, South Africa, and the Philippines, we make it happen for our clients, solving their biggest challenges with hyper-focused, domain-centered teams and cutting-edge tech, data, and analytics. Our real-world practitioners work collaboratively to deliver future-focused outcomes. Job Summary As a Machine Learning Engineer specializing in generative AI, you will be responsible for designing, developing, and deploying advanced machine learning models that generate high-quality, human-like content. You will collaborate with cross-functional teams to integrate these models into our products, enhancing their capabilities and delivering exceptional value to our clients. Key Responsibilities Develop, train, and optimize generative AI models for various applications, including text, image, and audio generation. Collaborate with product managers, software engineers, and data scientists to understand project requirements and deliver robust AI solutions. Conduct research to stay updated on the latest advancements in generative AI and apply best practices to improve model performance. Implement and maintain scalable machine learning pipelines for training and deploying models in production environments. Evaluate and fine-tune models to ensure they meet performance, accuracy, and efficiency standards. Perform data preprocessing, augmentation, and annotation to prepare high-quality datasets for model training. Troubleshoot and resolve issues related to model performance, data quality, and integration with other systems. Document model architecture, training processes, and performance metrics for internal and client-facing reports. Qualifications Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Proven experience in developing and deploying generative AI models using frameworks such as TensorFlow, PyTorch, or similar. Strong programming skills in Python and proficiency with machine learning libraries and tools. Familiarity with natural language processing (NLP), computer vision, and other relevant AI techniques. Experience with cloud platforms such as AWS, Google Cloud, or Azure for model deployment and management. Knowledge of data preprocessing, feature engineering, and model evaluation techniques. Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication skills to effectively convey technical concepts to non-technical stakeholders. Preferred Qualifications Experience with GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other advanced generative models. Understanding of ethical considerations and bias mitigation in AI systems. Contributions to open-source projects or publications in relevant conferences/journals. Experience with MLOps practices and tools for continuous integration and deployment of machine learning models.

About Us At NexusLink Services, we are passionate about building intelligent, scalable solutions that drive real-world impact. As we expand our AI/ML capabilities, we’re looking for a Generative AI-focused Data Scientist to join our innovative and rapidly growing team. Role Overview We are seeking an experienced Data Scientist with 4-6 years of hands-on experience and deep expertise in Generative AI to design and implement cutting-edge models that address real business challenges. You will work with LLMs, GANs, RAG frameworks, and transformer-based architectures to build scalable, production-ready solutions across industries. Key Responsibilities Design, develop, and fine-tune Generative AI models (LLMs, GANs, Diffusion models, etc.) Work on RAG (Retrieval-Augmented Generation) and transformer-based architectures Customize and fine-tune LLMs for domain-specific use cases Build and manage robust ML pipelines for training, evaluation, and deployment Collaborate with engineering teams to integrate models into real-world applications Stay updated with the latest GenAI research, tools, and trends Analyze model outputs, monitor performance, and ensure responsible AI use Required Skills 4-6 years of experience in data science or machine learning roles Strong Python skills with experience in ML/DL libraries: TensorFlow, PyTorch, HuggingFace Transformers Deep understanding of LLMs, GANs, RAG, Autoencoders, etc. Experience with LoRA, PEFT, or similar fine-tuning techniques Familiarity with Vector Databases (FAISS, Pinecone) and embeddings Expertise in data preprocessing, synthetic data generation Solid knowledge of NLP, prompt engineering, and language model safety Hands-on experience with model deployment, APIs, and cloud platforms (AWS/GCP/Azure) Nice to Have Experience with Chatbots, Conversational AI, or AI Assistants Familiarity with LangChain, LLMOps, or serverless model deployment Background in MLOps, Docker/Kubernetes, and CI/CD pipelines Exposure to OpenAI, Anthropic, Google Gemini, or Meta LLaMA

Endovision is a Med-tech company, which is helping the endoscopists to reduce cancer miss rate with the aid of real-time video analysis using AI. We are solving some of the hardest problems in the field of computer vision and deep learning and building end-to-end solutions for deep video understanding. Responsibilities We are looking to hire a new Research Engineer in our team. Your main responsibilities will be: Implementing state-of-the-art research papers, contributing to the company IP, and technology stack deployed in Nvidia embedded and dGPU Ecosystem. You’d work on cutting-edge deep learning, computer vision and spatio-temporal problems with an emphasis on endoscopy, with an opportunity to collaborate with research scientists and engineers at the Endovision and its partnering institutions. Implement/evaluate ideas, build and execute strategies to model hard video understanding problems, evaluate and benchmark end-to-end AI solutions in a collaborative team environment. Be part of and contribute to the evolution of AI Experimentation Lifecycle by focussing on experiment reusability and reproducibility. Requirements BSc/BA in Computer Science/ Eng., Engineering, Physics, Mathematics or relevant mathematically intensive fields Must have Computer vision/Image processing background with deep focus on deep learning (CNNs/GAN/vision transformers, etc.) Deep understanding in working of neural networks and its various aspects. Proven experience using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets. Must have good experience with pytorch . Prior experience with Nvidia Holoscan and Nvidia tensorrt is a plus Experience in machine-learning and operations research (ability to read, understand and reproduce solutions from leading research papers of the area). Knowledge of a variety of machine learning techniques (deep learning architectures, clustering, decision tree learning, random forests, ensembles etc.) and their real-world advantages/drawbacks. Knowledge of best practices / most common mistakes in designing and implementing Machine Learning systems, mature instinct / intuition for real problem diagnostics and solving. Must have experience (academic or industry) with Computer Vision and Deep Learning in at least two of:- Neural networks - CNNs, RNNs, autoencoders, transfer learning, numerical optimization, etc. Comfortable working within an agile and iterative prototyping in startups.

Endovision is dedicated to enhancing the diagnostic accuracy of upper GI endoscopists through the use of deep learning and computational modeling, ultimately contributing to improved healthcare outcomes. As a Data Science Intern based in New Delhi, you will play a crucial role in developing end-to-end machine learning models to address real-world challenges within the industry. In this on-site internship position, you will work on implementing cutting-edge AI technologies, leveraging state-of-the-art research papers, and contributing to the company's intellectual property. You will be involved in building AI-first products and collaborating with research scientists and engineers at Endovision and its partner institutions. The primary focus areas will include deep learning, computer vision, and graphics, particularly in the context of endoscopy. Ideal candidates for this role should possess experience in Computer Vision and Deep Learning, with a strong foundation in neural networks such as CNNs, RNNs, autoencoders, and transfer learning methods. Proficiency in Python and its scientific libraries, familiarity with Machine Learning techniques, and knowledge of Deep Learning frameworks like Keras, TensorFlow, and PyTorch are essential requirements. Strong analytical and problem-solving skills, along with excellent communication abilities, are key attributes for success in this role. Candidates pursuing a Bachelor's or Master's degree in Computer Science, Statistics, or a related field are encouraged to apply. Experience with end-to-end machine learning projects would be advantageous. Preferred candidates will have the ability to independently implement and evaluate ideas using modern deep learning tools like Python, PyTorch, and GPU-enabled compute. Additionally, having a track record of implementing or publishing research papers in reputable academic conferences related to deep learning and computer vision applications will be highly valued. A positive attitude, strong teamwork skills, and effective communication capabilities are essential qualities for individuals joining our dynamic team at Endovision.,