{"id":651528,"url":"https://alion.io/job/encora-machine-learning-specialist","title":"Machine Learning Specialist","company":{"id":710119,"name":"Coforge","domain":"coforge.com","url":"https://alion.io/company/coforge-3","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":80,"open_postings":36,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-09-25T05:45:01Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Makati, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":50000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":456},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Data Augmentation","optional":false},{"name":"Docker","optional":false},{"name":"DVC","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Git","optional":false},{"name":"JAX","optional":false},{"name":"Kubernetes","optional":false},{"name":"LoRA","optional":false},{"name":"Machine Learning","optional":false},{"name":"PEFT","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"QLoRA","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"GCP","optional":true},{"name":"NLP","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Transformers","optional":true}],"status":"closed","first_seen_at":"2026-08-14T02:28:24Z","employer_posted_date":"2026-08-14","last_verified_at":"2026-09-25T19:45:05Z","board_verified":false,"closed_at":"2026-09-25T19:45:05Z","days_open":42,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":42},"description":"Position Title: Machine Learning Specialist (Research & Engineering)\nWork Location: BGC, Taguig City. (2 x onsite per week hybrid set up)\nWe are seeking a versatile Machine Learning Specialist to own the end-to-end lifecycle of AI development. This role is designed for a technical expert who can navigate the entire spectrum of machine learning-from conducting state-of-the-art research and fine-tuning foundational models to architecting the production-grade pipelines and APIs that bring these models to life. You will bridge the gap between theoretical innovation and scalable business impact, ensuring our AI solutions are both cutting-edge and operationally robust.\nKey Responsibilities\nThe following are key areas of responsibility, but not limited to the ff:\nResearch & Experimental Innovation\nAdvanced Research: Conduct deep-dive research into state-of-the-art (SOTA) architectures and foundational models to solve complex business problems like credit scoring, fraud detection, and personalization.\nModel Optimization: Execute rigorous hyperparameter tuning and fine-tuning techniques (e.g., PEFT, LoRA, QLoRA) to maximize model accuracy and efficiency.\nBenchmarking & Evaluation: Develop comprehensive evaluation frameworks and leaderboards to monitor model accuracy and compare experimental iterations.\nData Strategy & Engineering\nPipeline Design: Lead the design of experimentation datasets and production data pipelines, focusing on feature engineering and data augmentation.\nData Quality: Ensure high-quality data inputs for both training and real-time inference, collaborating with data squads to maintain data integrity.\nProduction Engineering & MLOps\nDeployment & Orchestration: Architect and manage the end-to-end deployment of models using containers (Docker, Kubernetes) and CI/CD pipelines.\nSystem Integration: Build robust APIs to integrate AI models with internal platforms and refactor research code into production-grade, low-latency, and high-throughput codebases.\nModel Governance: Implement MLOps best practices, including versioning (DVC), drift detection, and automated \"quality gates\" to ensure alignment with internal KPIs and regulatory standards.\nSquad Collaboration & Agile Delivery\nActive Squad Collaboration: Work as a core member of a cross-functional squad, aligning daily with Data Engineers, Backend Developers, and Product Owners to ensure seamless product integration.\nAgile Participation: Drive technical value within Agile ceremonies (Stand-ups, Sprints, Retrospectives) by translating high-level business requirements into executable research hypotheses and production-ready sprints.\nDocumentation & Knowledge Leadership\nTechnical Documentation: Author and maintain the full technical stack documentation, ranging from scientific research findings and experimental logs to system architecture diagrams and deployment guides.\nPeer Mentoring: Act as a technical subject matter expert by mentoring squad members, conducting code reviews, and fostering an internal culture of AI literacy and \"New Ways of Working.\"\nMinimum Requirements\nEducation: Undergraduate degree in a quantitative field (e.g., Computer Science, Statistics,Information Technology or Physics, or Mathematics). A Graduate degree (Master’s or PhD) is highly preferred for the research component.\nExperience: 3+ years in a functionally similar role (Data Science, ML Research, or ML Engineering).\nTechnical Proficiency: * Expert-level Python and SQL.\nStrong experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX).\nHands-on experience with Git, CI/CD, and MLOps tools.\nMindset: A strong bias toward model explainability and security.\nPreferred Skills\nPortfolio: A demonstrable portfolio of advanced AI use cases (e.g., GenAI, NLP, Recommender Systems, or Graph Algorithms).\nCloud Infrastructure: Familiarity with AWS, GCP, or Azure AI services.\nPublications: Published research in relevant AI/ML conferences or journals.","description_format":"text","description_chars":3937,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Cybersecurity","Science & Engineering"],"lifecycle":[{"event":"open","at":"2026-09-10T20:32:59Z"},{"event":"close","at":"2026-09-25T19:45:05Z"}],"liveness":null,"pay":null,"html_url":"https://alion.io/job/encora-machine-learning-specialist","json_url":"https://alion.io/job/encora-machine-learning-specialist.json","meta":{"generated_at":"2026-09-26T03:20:03Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3563,"day_limit":5000,"remaining_today":1437,"minute_limit":60,"resets_at":"2026-09-27T00:00:00Z"}}}