{"id":1046905,"url":"https://alion.io/job/mattel-software-engineer-aiml","title":"Software Engineer - AI/ML","company":{"id":13477,"name":"Mattel","domain":"mattel.com","url":"https://alion.io/company/mattel-inc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":10,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":24,"computed_at":"2026-10-01T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19500,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Computer Vision","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"Image Segmentation","optional":false},{"name":"LightGBM","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OCR","optional":false},{"name":"OpenCV","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Tool Use","optional":false},{"name":"Transformers","optional":false},{"name":"XGBoost","optional":false},{"name":"YOLO","optional":false},{"name":"Agile","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LlamaIndex","optional":true},{"name":"MLFlow","optional":true},{"name":"NumPy","optional":true},{"name":"Pandas","optional":true},{"name":"Python","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Semantic Kernel","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-09-18T12:10:32Z","employer_posted_date":"2026-09-18","last_verified_at":"2026-10-01T10:20:36Z","board_verified":true,"closed_at":null,"days_open":13,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":13},"description":"CREATIVITY IS OUR SUPERPOWER. It’s our heritage and it’s also our future. Because we don’t just make toys. We create innovative products and experiences that inspire fans, entertain audiences and develop children through play. Mattel is at its best when every member of our team feels respected, included, and heard-when everyone can show up as themselves and do their best work every day. We value and share an infinite range of ideas and voices that evolve and broaden our perspectives with a reach that extends into all our brands, partners, and suppliers.\n We are looking for a Data Scientist - ML & Generative AI with strong hands-on experience across traditional Machine Learning, Deep Learning, Generative AI, and Computer Vision. The ideal candidate will be able to translate business problems into scalable AI/ML solutions and take models from experimentation through production deployment.\nThe role will have a particular focus on building AI solutions for Supply Chain, Operations, Forecasting, Optimization, and Vision-based use cases. The candidate should be comfortable working with structured, unstructured, image, and text data and collaborating with business, engineering, product, and data teams.\nKey Responsibilities\nMachine Learning & Predictive Analytics\nDesign, develop, and evaluate machine learning models for classification, regression, forecasting, clustering, recommendation, anomaly detection, and optimization problems.\nApply statistical and machine learning techniques such as Linear/Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost/LightGBM, clustering, and time-series modeling.\nPerform feature engineering, feature selection, model tuning, validation, and performance analysis.\nBuild reusable and scalable ML pipelines for real-world business applications.\nDeep Learning\nDevelop deep learning solutions using frameworks such as PyTorch and/or TensorFlow.\nWork with neural network architectures including CNNs, RNN/LSTMs, Transformers, and other modern deep learning architectures.\nEvaluate and optimize deep learning models for accuracy, latency, and scalability.\nGenerative AI & LLMs\nDesign and develop GenAI applications leveraging Large Language Models (LLMs).\nBuild solutions using techniques such as:Prompt engineering\nRetrieval-Augmented Generation (RAG)\nEmbeddings and vector search\nLLM orchestration\nFunction/tool calling\nAI agents and multi-step workflows\nFine-tuning / parameter-efficient fine-tuning where appropriate\n\nWork with structured and unstructured enterprise data to create domain-specific GenAI applications.\nDevelop evaluation frameworks for LLM applications covering response quality, hallucination, groundedness, relevance, latency, and cost.\nImplement appropriate guardrails and responsible AI practices for production GenAI solutions.\nComputer Vision\nDevelop and deploy computer vision solutions for use cases such as:Image classification\nObject detection\nImage segmentation\nOCR and document/image understanding\nVisual inspection and defect detection\nProduct/image recognition\n\nWork with modern computer vision architectures and pretrained/foundation models.\nExperience with OpenCV, YOLO, CNNs, Vision Transformers, or multimodal models is desirable.\nSupply Chain & Operations Analytics\nDevelop AI/ML solutions addressing supply-chain and operational problems such as:\nDemand forecasting\nSales forecasting\nInventory optimization\nStock-out / overstock prediction\nReplenishment recommendations\nLead-time prediction\nSupply and demand imbalance detection\nLogistics and transportation analytics\nETA prediction\nWarehouse analytics\nSupplier performance and risk analytics\nProduct allocation and assortment optimization\nAnomaly detection\nScenario planning and decision-support solutions\nThe candidate should be able to work closely with supply-chain stakeholders to convert business requirements into analytical and AI/ML solutions.\nModel Deployment & MLOps\nCollaborate with engineering teams to deploy ML and GenAI solutions into production.\nDevelop APIs, batch pipelines, or real-time inference services for model consumption.\nApply good software engineering practices including modular development, version control, testing, documentation, and code reviews.\nUnderstand concepts such as model monitoring, drift detection, model versioning, experimentation, and retraining.\nExperience with Docker, CI/CD, MLflow, Kubernetes, or similar MLOps technologies is desirable.\nRequired Technical Skills\nProgramming\nStrong Python programming skills\nSQL and data manipulation\nPandas, NumPy, Scikit-learn\nMachine Learning\nScikit-learn\nXGBoost / LightGBM or equivalent\nStatistical modeling\nTime-series forecasting\nFeature engineering and model evaluation\nDeep Learning\nPyTorch and/or TensorFlow\nTransformers\nCNNs and modern neural-network architectures\nGenerative AI\nLLMs and foundation models\nRAG\nPrompt engineering\nEmbeddings\nVector databases\nLLM evaluation\nAgentic AI concepts\nFrameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent\nComputer Vision\nOpenCV\nObject detection / segmentation models\nCNNs / Vision Transformers\nOCR and image-processing techniques\nData & Cloud\nExperience working with large datasets and cloud-based data platforms.\nExposure to AWS, Azure, or GCP.\nFamiliarity with Databricks, Spark, Snowflake, or similar platforms is an advantage.\nQualifications & Experience\nBachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline.\nApproximately 4-7 years of relevant industry experience in Data Science, Machine Learning, or AI.\nStrong hands-on experience developing end-to-end ML solutions.\nPractical experience with at least one of Generative AI, Computer Vision, or advanced Deep Learning, with willingness and ability to work across all areas.\nExperience solving supply-chain, retail, manufacturing, logistics, or operations-related problems is strongly preferred.\nExperience taking ML models beyond proof-of-concept into production or business adoption.\nWhat We Are Looking For\nThe successful candidate will demonstrate:\nStrong problem-solving and analytical thinking.\nSolid understanding of ML fundamentals rather than reliance solely on pre-built GenAI APIs.\nAbility to select the right approach across statistical methods, traditional ML, deep learning, computer vision, and GenAI based on the business problem.\nAbility to communicate complex analytical concepts to both technical and non-technical stakeholders.\nStrong experimentation mindset with an ability to measure business and model impact.\nCuriosity to continuously learn and apply emerging AI technologies.\nAbility to independently own moderately complex projects while collaborating effectively with senior data scientists, engineers, product teams, and business stakeholders.\nPreferred / Good-to-Have Experience\nExperience with retail, consumer products, manufacturing, or supply-chain domains.\nExperience building production-grade RAG or enterprise GenAI applications.\nExposure to multimodal AI combining text, image, and structured data.\nExperience with optimization / operations research techniques.\nExperience with forecasting at scale across products, locations, or customers.\nKnowledge of responsible AI, explainability, privacy, and AI governance.\nExperience working in Agile product or AI development teams.\n Don’t meet every single requirement? At Mattel, we are dedicated to an inclusive workplace and a culture of belonging. If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we still encourage you to apply. You may be just the right candidate for this or other roles.\nHow We Work:\nWe are a purpose driven company aiming to empower generations to explore the wonder of childhood and reach their full potential. We live up to our purpose employing the following behaviors:\nWe collaborate: Being a part of Mattel means being part of one team with shared values and common goals. Every person counts and working closely together always brings better results. Partnership is our process and our collective capabilities is our superpower.\nWe innovate: At Mattel we always aim to find new and better ways to create innovative products and experiences. No matter where you work in the organization, you can always make a difference and have real impact. We welcome new ideas and value new initiatives that challenge conventional thinking.\nWe execute: We are a performance-driven company. We strive for excellence and are focused on pursuing best-in-class outcomes. We believe in accountability and ownership and know that our people are at their best when they are empowered to create and deliver results.\nOur Approach to Flexible Work:\nWe embrace a flexible work model designed to empower a culture of growth, optimism, and wellbeing, where every employee can reach their full potential. Combining purposeful in-person collaboration with flexibility, our focus is to optimize performance and drive connection for moments that matter.\nWho We Are:\nMattel is a leading global toy and family entertainment company and owner of one of the most iconic brand portfolios in the world. We engage consumers and fans through our franchise brands, including Barbie, Hot Wheels, Fisher-Price, American Girl, Thomas & Friends, UNO, Masters of the Universe, Matchbox, Monster High, MEGA and Polly Pocket, as well as other popular properties that we own or license in partnership with global entertainment companies. Our offerings include toys, content, consumer products, digital and live experiences. Our products are sold in collaboration with the world’s leading retail and ecommerce companies. Since its founding in 1945, Mattel is proud to be a trusted partner in empowering generations to explore the wonder of childhood and reach their full potential.\nMattel’s award-winning workplace culture has been recognized by Forbes, Fast Company, Newsweek, Great Place to Work, TIME, and more.\nVisit us at https://jobs.mattel.com/ and www.instagram.com/MattelCareers.\nMattel is an Equal Opportunity Employer where we want you to bring your authentic self to work every day. We welcome all job seekers, and all applicants will receive consideration for employment.\nVideos to watch:\nThe Culture at Mattel\nCorporate Philanthropy","description_format":"text","description_chars":10394,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Flexible schedule"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Toys, Games & Puzzles"],"lifecycle":[{"event":"open","at":"2026-09-18T22:11:25Z"}],"liveness":{"score":53,"band":"ok","label":"Likely open","p_open":1,"p_active":0.583,"p_room":0.9,"age_days":12,"expected_fill_days":24,"reasons":["conf:26","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/mattel-software-engineer-aiml","json_url":"https://alion.io/job/mattel-software-engineer-aiml.json","meta":{"generated_at":"2026-10-01T18:23:25Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":718,"day_limit":5000,"remaining_today":4282,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}