{"id":3798380,"url":"https://alion.io/job/philips-data-scientist-computer-vision","title":"Data Scientist - Computer Vision","company":{"id":13838,"name":"Philips","domain":"philips.com","url":"https://alion.io/company/philips-2","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":85,"open_postings":74,"ghost_share":0,"stale_share":0.797,"repost_share":0,"time_to_fill_p50_days":15,"computed_at":"2026-11-05T05:54:30Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Computer Vision","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"OpenCV","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"YOLO","optional":false}],"status":"live","first_seen_at":"2026-11-05T10:26:38Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-05T22:06:27Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Job Title\nData Scientist - Computer VisionJob Description\nKey Responsibilities\nAI/ML solution development\n· Translate consumer, product and business challenges into well-defined Data Science and AI problems.\nAnalyse complex and high-dimensional datasets and formulate hypotheses and proof-of-concepts.\nDesign, develop and evaluate Machine Learning and Deep Learning models.\nBuild solutions using Computer Vision, NLP, Generative AI and LLM-based techniques, depending on the use case.\nEvaluate state-of-the-art AI/ML approaches and apply appropriate techniques to complex business problems. \nComputer Vision & Deep Learning\n· Develop AI-based Computer Vision applications for image-related use cases.\nApply modern deep-learning architectures and frameworks, including approaches such as YOLO and U-Net, where appropriate.\nWork with image-processing and feature-extraction techniques and develop robust model-training and evaluation pipelines.\nGenerative AI & NLP\n· Develop solutions using LLMs, Transformers, RAG architectures and agentic frameworks.\nApply NLP approaches for extracting and representing information from unstructured data.\nEvaluate GenAI solutions for quality, reliability and suitability for the intended application. \nData & experimentation\n· Perform exploratory data analysis, data cleansing, preprocessing, feature engineering and statistical analysis.\nEnsure data quality, accuracy and reliability through validation and quality-control approaches.\nEstablish reproducible methodologies and document experiments, assumptions, results and analytical findings. \nProductionisation & MLOps\n· Participate in the end-to-end deployment and testing of Data Science solutions.\nWork closely with engineering teams to integrate AI models into production applications and enterprise workflows.\nMonitor and continuously improve deployed model performance.\nContribute to robust and scalable data pipelines supporting advanced analytics and ML solutions. \nCollaboration & technical contribution\n· Collaborate with Data Engineers, Software Engineers, product/business stakeholders and other cross-functional teams to operationalise Data Science solutions.\nCommunicate complex analytical results and recommendations clearly to stakeholders.\nContribute to knowledge sharing, technical documentation and Data Science methodologies.\nMentor Data Scientists and contribute to building Data Science competency within the organisation\nYou're the right fit if:\n7-10 years experience in AI and Data Science field\nMaster's in computers, electronics, electrical engineering or PhD in relevant streams \nStrong hands-on experience in several of the following:\nPython and Data Science/ML ecosystem\nMachine Learning and statistical modelling\nDeep Learning\nPyTorch / TensorFlow\nComputer Vision and OpenCV\nImage processing and AI-based vision applications\nNLP and Transformer\nLLMs and Generative AI\n Retrieval-Augmented Generation (RAG)\nAgentic AI frameworks\nClassical ML approaches such as regression, Random Forest, SVM and k-NN\nStatistical testing and experimental analysis\nData preparation, validation and quality assessment\nHow we work together\nWe believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.\nthis role is an office role.\nAbout Philips\nWe are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.\nLearn more about our business.\nDiscover our rich and exciting history.\nLearn more about our purpose. If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. 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