{"id":169275,"url":"https://alion.io/job/minfy-technologies-senior-ai-developer-2","title":"Senior AI Developer","company":{"id":59584,"name":"Minfy Technologies","domain":"minfytech.com","url":"https://alion.io/company/minfy-technologies","size_band":"201-500","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"B","score":83,"open_postings":17,"ghost_share":0,"stale_share":0.471,"repost_share":0,"time_to_fill_p50_days":68,"computed_at":"2026-10-30T05:48:23Z"}},"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":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":2500000,"max":3200000,"currency":"INR","period":"year","gross":null,"usd_annual":33811},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Amazon CloudWatch","optional":true},{"name":"Feature Store","optional":true},{"name":"LLM","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-06-04T09:22:14Z","employer_posted_date":"2026-06-04","last_verified_at":"2026-10-30T16:20:14Z","board_verified":true,"closed_at":null,"days_open":148,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":146},"description":"Job Summary\nThe Senior AI/ML Engineer is responsible for building, integrating, and operationalizing the machine learning components of the Topic Ranking personalization solution. This role focuses on feature engineering, model enhancement, pipeline development, GenAI integration, deployment, and production-readiness across the training and serving lifecycle.\nKey Responsibilities\nDevelop and enhance the ranking model using the existing SharedBottomModel and multi-task learning framework.\nEngineer user-level behavioral features from ordering and interaction data.\nIntegrate GenAI-generated user profile features and embeddings into model training and inference workflows.\nBuild and adapt ETL pipelines for feature extraction, transformation, and profile generation.\nImplement projection layers, gating mechanisms, and preprocessing logic for embedding-based features.\nExecute model training, offline validation, and hyperparameter optimization workflows.\nApply techniques such as inverse propensity scoring to address ranking bias.\nDeploy trained models to SageMaker endpoints and validate integration with the serving platform.\nSupport shadow-mode validation, monitoring, model drift awareness, and operational readiness.\nProduce technical documentation and runbooks for deployment, retraining, and support handoff. \nRequired Skills\nStrong hands-on experience in machine learning engineering and production ML deployment.\nProficiency in Python, PySpark, and ML pipeline development.\nExperience with Amazon SageMaker for training, tuning, batch processing, and endpoint deployment.\nFamiliarity with feature engineering for recommendation or ranking systems.\nStrong understanding of embeddings, model integration patterns, and model-serving considerations.\nExperience working with distributed data pipelines, cloud storage, and production data environments.\nAbility to troubleshoot end-to-end ML workflows across data preparation, training, deployment, and monitoring. \nPreferred Qualifications\nExperience integrating GenAI or LLM-generated outputs into downstream ML systems.\nFamiliarity with feature stores, batch inference pipelines, and retraining orchestration.\nExperience supporting online experimentation or shadow deployments in production systems.\nExposure to operational monitoring tools such as CloudWatch or model monitoring solutions.\nPrior experience in personalization, marketplace platforms, or consumer recommendation products.","description_format":"text","description_chars":2448,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Managed IT Services (MSP)","AI Consulting & Integration","Cloud Consulting & Migration","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-08-29T21:18:52Z"}],"visa":[],"liveness":{"score":20,"band":"cold","label":"Long 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