{"id":3919491,"url":"https://alion.io/job/oxiliry-lead-aiml-engineer","title":"Lead AI/ML Engineer","company":{"id":4523141,"name":"Oxiliry","domain":"oxiliry.com","url":"https://alion.io/company/oxiliry","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Karachi, Pakistan"],"countries":["PK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Computer Vision","optional":false},{"name":"GCP","optional":false},{"name":"Kubeflow","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-11-07T14:02:15Z","employer_posted_date":"2026-11-07","last_verified_at":"2026-11-07T22:21:08Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Group\nOxiliry is a trusted business process outsourcing partner, providing quality resources and delivering scalable, efficient, and innovative solutions to empower businesses globally. Committed to excellence, we streamline operations to drive profitability, foster sustainable growth, and build lasting partnerships for success.\nRequirements\nKey Responsibilities\nAI/ML Model Development & Deployment\nDesign, develop, and deploy machine learning and deep learning models for production environments.\nBuild and optimize data pipelines for training, validation, and inference.\nImplement NLP, computer vision, predictive analytics, or recommendation systems as required.\nEnsure model scalability, performance, and security.\nConduct model evaluation, tuning, and performance bench marking.\nCross-Functional Collaboration\nWork closely with Software Engineers, CMS teams, and Frontend developers for AI feature integration.\nCoordinate with DBA and DevOps teams for data management, cloud deployment, and MLOps practices.\nCollaborate with QA/SQA teams to ensure model validation, monitoring, and reliability.\nSupport PMO in technical estimations, sprint planning, and requirement clarifications.\nArchitecture & Optimization\nDesign scalable AI system architectures (including microservices or headless AI integrations where applicable).\nOptimize algorithms for speed, accuracy, and resource utilization.\nImplement monitoring systems for model drift, bias detection, and performance tracking.\nDevelop reusable AI components and standardized ML workflows.\nMentorship & Knowledge Sharing\nProvide technical mentorship to junior AI/ML engineers and data scientists.\nAssist Lead Engineer in reviewing model code, experimentation frameworks, and best practices.\nContribute to internal AI documentation, research notes, and knowledge repositories.\nQualifications\nMust Have\nBachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.\n4-6 years of hands-on experience in AI/ML development.\nStrong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).\nExperience with data preprocessing, feature engineering, and model optimization techniques.\nKnowledge of REST APIs and integration of ML models into production systems.\nFamiliarity with Agile methodologies and SDLC processes.\nPreferred\nExperience with MLOps tools (MLflow, Kubeflow, SageMaker, etc.).\nKnowledge of cloud platforms (AWS, Azure, or GCP) for AI deployment.\nExperience in LLMs, Generative AI, or enterprise AI implementations.\nExposure to SaaS-based AI solutions.\nRelevant AI/ML certifications.\nJoin Us\nBe part of Oxiliry and contribute to building scalable, efficient, and innovative AI solutions while collaborating with cross-functional teams and advancing AI/ML 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