{"id":3239350,"url":"https://alion.io/job/onepint-ai-ml-engineer","title":"ML Engineer","company":{"id":4473535,"name":"OnePint.ai","domain":"onepint.ai","url":"https://alion.io/company/onepint-ai","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":null,"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":{"min_usd":11500,"max_usd":30000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":18},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Time Series","optional":false},{"name":"XGBoost","optional":false},{"name":"LLM","optional":true}],"status":"live","first_seen_at":"2026-10-25T14:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-25T14:35:00Z","board_verified":false,"closed_at":null,"days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"description":"Responsibilities: \nYou'll architect intelligent systems that sense demand shifts in real time and recommend actions before a human even asks.\nAgentic AI pipelines that go beyond prediction systems that reason, decide, and adapt autonomously.\nAdvanced demand forecasting and sensing models using attribute-based and cohort-based approaches.\nSignal integration frameworks that fuse external data and real-time market inputs.\nFeature engineering at scale: lag structures, rolling aggregations, and derived features.\nModel performance frameworks tied directly to measurable business outcomes.\nTranslating complex model insights into clear, actionable language for clients and leadership.\n\nKey Performance Indicators: \nModel accuracy, reliability, and real-world forecast performance.\nSpeed and quality of model deployment to production pipelines.\nBusiness impact of AI-driven recommendations measured in inventory efficiency and revenue outcomes.\nCross-functional collaboration effectiveness with product, engineering, and client teams.\n\nRequirements: \nYou bring a strong foundation in machine learning and a genuine curiosity about where AI is heading.\n2-6 years of hands-on experience in ML, AI, or Data Science with a proven model-building track record.\nPython fluency: pandas, scikit-learn, XGBoost, and LightGBM are second nature to you.\nDeep understanding of time series forecasting and experience with large-scale transactional datasets.\nAbility to connect model outputs to real business impact and articulate the 'so what' clearly.\nGenuine curiosity about the power of AI and openness to emerging tools and paradigms, including agentic and generative AI.\n\nBonus Points: \nExperience in retail, supply chain, or inventory planning domains.\nExposure to hierarchical forecasting, new product forecasting, or ensemble methods.\nHands-on work with LLM-based agents or orchestration frameworks.\nSkills\nAI, ML, artificial intelligence, data science, forecasting, lightgbm, machine learning, pandas, python, scikit-learn, time series, 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