{"id":2501473,"url":"https://alion.io/job/nielseniq-machine-learning-engineer-2","title":"Machine Learning Engineer","company":{"id":9378,"name":"NielsenIQ","domain":"nielseniq.com","url":"https://alion.io/company/nielseniq","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":15,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":14,"computed_at":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Vadodara, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":9500,"max_usd":24000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AutoGen","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"GitHub","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"NLTK","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false},{"name":"Azure","optional":true},{"name":"MLFlow","optional":true}],"status":"closed","first_seen_at":"2026-10-14T04:17:16Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T09:16:41Z","board_verified":false,"closed_at":"2026-10-15T09:16:41Z","days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Job Description\nKey Responsibilities:\nModel Development: Design, develop, and fine-tune Machine Learning Models\nGenerative AI: Implement Generative AI use cases using frameworks like LangChain, AutoGen, CrewAI etc\nResearch: Conduct research to advance the state-of-the-art in generative AI, including exploring new algorithms, techniques, and tools.\nCollaboration: Work along with Seniors and Stake holders to capture the requirements and execute it in Agile methodology.\nDocumentation: Maintain comprehensive documentation of models, experiments, and findings to facilitate knowledge sharing and reproducibility.\nStay Updated: Keep abreast of the latest developments in the field of AI and machine learning and apply this knowledge to current projects.\nQualifications\nGraduate with hands on expeience in Machine Learning\nMust Have:\nProficiency in Python Programming Language\nMin 2+ years of experience\nExperience in Developing Machine Learning models using Sklearn/PyTorch/TensorFlow\nExperience with Natural Language Processing (NLP) libraries and tools such as Spark NLP, Hugging Face, NLTK etc.\nExperience in any GenAI framework such as LangChain, AutoGen or CrewAI etc\nExperience in Github and CI/CD pipelines to deploy the Machine Learning Models\nGood to Have:\nExperience in MLOps Tools like MLflow, AutoML etc\nExperience in Azure Cloud\nExperience in working Agile Model.\n Our Benefits\nFlexible working environment\nVolunteer time off\nLinkedIn Learning\nEmployee-Assistance-Program (EAP)\nNIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/\nAbout NIQ\nNIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights-delivered with advanced analytics through state-of-the-art platforms-NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.\nFor more information, visit NIQ.com\nWant to keep up with our latest updates?\nFollow us on: LinkedIn | Instagram | Twitter | Facebook\nOur commitment to Diversity, Equity, and Inclusion\nAt NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. 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