{"id":1107931,"url":"https://alion.io/job/quantiphi-senior-machine-learning-engineer-6","title":"Senior Machine Learning Engineer","company":{"id":6155,"name":"Quantiphi","domain":"quantiphi.com","url":"https://alion.io/company/quantiphi","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":88,"open_postings":65,"ghost_share":0,"stale_share":0.462,"repost_share":0.015,"time_to_fill_p50_days":34,"computed_at":"2026-11-12T10:38:37Z"}},"role":"AI/ML","role_family":"AI/ML","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","Mumbai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":24000,"max_usd":49000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Docker","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"Statsmodels","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false},{"name":"Transformers","optional":false},{"name":"CNN","optional":true},{"name":"Computer Vision","optional":true},{"name":"OpenCV","optional":true}],"status":"live","first_seen_at":"2026-09-22T07:36:09Z","employer_posted_date":"2026-09-22","last_verified_at":"2026-11-13T15:05:44Z","board_verified":true,"closed_at":null,"days_open":52,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":51},"description":"While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.\nIf working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!\nMachine Learning Engineer with 4-6 years of experience, specializing in time-series forecasting. He/she will lead data preparation and profiling efforts to design, build, and deploy predictive models for demand planning and forecasting. Experience in the retail domain is a strong plus. This role requires readiness to travel to our client office in Bengaluru twice a week.\nMust have Skills:\n4-6 years of hands-on experience in Machine Learning / Data Science.\n\nStrong expertise in time-series forecasting and handling sequential data.\n\nBuild, evaluate, and tune statistical and ML-based forecasting models (ARIMA, LightGBM, Prophet, LSTMs/Transformers).\n\nSolid experience in data preparation, data quality assessment, and exploratory data analysis (EDA) on raw, large-scale datasets.\n\nAdvanced proficiency in Python and SQL.\n\nProven ability to work independently as a solo team member with minimal supervision, taking end-to-end ownership of tasks from data preparation to model development and deployment.\n\nAbility to speak to customer confidently to present his/her own work not only in pure technical terms but also from a functional or business perspective.\n\nExperience with AWS Cloud Platform and services\n\nSagemaker ***\n\nHands-on experience with ML frameworks (pandas, scikit-learn, PyTorch/TensorFlow, statsmodels, Prophet) and MLOps tools (Docker, Airflow, MLflow).\n\nGood to have skills:\nPrior experience in Retail / E-Commerce (e.g., demand planning, SKU-level forecasting, stockout prediction).\n\nComputer Vision Experience: Exposure to basic computer vision tasks, image preprocessing, and classification using tools like OpenCV, PIL, or CNN frameworks (e.g., handling visual data, planograms, or shelf-monitoring images in retail).\n\nOther:\nCollaborate with multiple Business stakeholders and understand their business requirements\n\nGood verbal and written communication in English\n\nIf you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with 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