{"id":961728,"url":"https://alion.io/job/brillio-senior-aiml-engineer-r01570503","title":"Senior AI/ML Engineer - R01570503","company":{"id":3063,"name":"Brillio","domain":"brillio.com","url":"https://alion.io/company/brillio","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":76,"open_postings":42,"ghost_share":0,"stale_share":0.952,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","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":20000,"max_usd":41000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"BentoML","optional":false},{"name":"Evidently AI","optional":false},{"name":"GCP","optional":false},{"name":"Great Expectations","optional":false},{"name":"Interpretability","optional":false},{"name":"Keras","optional":false},{"name":"Kubeflow","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"AI Agents","optional":true},{"name":"pySpark","optional":true},{"name":"SAS","optional":true},{"name":"Spark","optional":true},{"name":"SPSS","optional":true}],"status":"live","first_seen_at":"2026-09-16T09:26:21Z","employer_posted_date":"2026-09-16","last_verified_at":"2026-11-02T21:27:22Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":47},"description":"Senior AI/ML Engineer\nJob requirements\nExperience Range: With at least 2 to 4 years of hands-on experience in advanced data science, machine learning, and AI engineering roles Key Responsibilities:\nDesign and develop advanced machine learning models using classic algorithms and deep learning techniques to address complex business challenges and deliver measurable improvements\nConduct comprehensive exploratory data analysis (EDA) and statistical analysis, including hypothesis testing, regression, and classification, to extract actionable insights from large datasets\nImplement, optimize, and deploy AI/ML models on Google Cloud Platform (GCP), ensuring scalability, reliability, and efficient integration into production environments\nCollaborate with cross-functional teams to define data requirements, validate model outputs, and integrate AI solutions seamlessly into existing workflows\nUtilize KubeFlow and BentoML for efficient model orchestration, deployment, and monitoring, ensuring robust operational performance\nPerform rigorous forecasting using methods such as exponential smoothing, ARIMA, and ARIMAX to support data-driven business planning\nApply probabilistic graph models and advanced statistical methods to enhance predictive accuracy and interpretability of AI solutions\nMaintain high standards for data quality and model performance using frameworks like Great Expectations and Evidently AI, tracking key metrics and outcomes\nRequired Skills:\nProficiency in Python and SQL for data manipulation, analysis, and model development\nHands-on experience with classic machine learning algorithms and deep learning frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet\nExpertise in statistical analysis including hypothesis testing, T-Test, Z-Test, and regression (linear, logistic)\nExperience with classification techniques such as decision trees and support vector machines (SVM)\nKnowledge of forecasting methods including exponential smoothing, ARIMA, and ARIMAX\nAbility to implement and interpret probabilistic graph models\nFamiliarity with tools for model deployment and orchestration such as KubeFlow and BentoML\nCompetence in computing and analyzing distance metrics (Hamming, Euclidean, Manhattan)\nExperience with data quality frameworks such as Great Expectations and Evidently AI\nPreferred Skills:\nExperience with GenAI and Agentic AI technologies\nHands-on expertise with PySpark, SAS, or SPSS for large-scale statistical computing\nProficiency in R and R Studio for statistical modeling and data visualization\nDesired Qualifications:\nBachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline\nCertification in machine learning or data science from recognized platforms such as TensorFlow Developer Certificate or Google Professional Machine Learning Engineer\nCertification in cloud technologies, for example Google Cloud Certified - 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