{"id":3312657,"url":"https://alion.io/job/gramian-consulting-group-machine-learning-research-engineering-specialist-3","title":"Machine Learning Research & Engineering Specialist","company":{"id":5702,"name":"Gramian Consulting Group","domain":"gramianconsultinggroup.com","url":"https://alion.io/company/gramianconsultinggroup","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AR","BR","CO","CL","PE","UY"],"hiring_countries_total":6,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-26T00:00:00Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-30T02:48:08Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"About Gramian\nGramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.\nAbout the Role\nWe are seeking a highly skilled Machine Learning Research & Engineering Specialist to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, and performance optimization. This is a coding-intensive role requiring hands-on experience with Python, machine learning engineering, and coding agents integrated into development workflows. You will build, modify, debug, and validate machine learning implementations, create reproducible training and inference pipelines, and optimize systems for correctness, memory usage, and throughput. The ideal candidate combines strong quantitative foundations with practical coding skills and experience solving complex machine learning engineering problems.\nSENIORITY: Experienced / Research-Level Engineer\nEDUCATION: Master's degree or PhD in a relevant quantitative discipline\nLANGUAGE: Strong written and verbal English\nLOCATION: Remote - Worldwide\nKey Responsibilities\nDevelop, implement, and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.\n\nImplement or modify model components, data pipelines, evaluation systems, and numerical methods using Python.\n\nBuild reproducible programmatic workflows using Python, command-line tools, and relevant machine learning frameworks.\n\nDebug numerical, algorithmic, and system-level failures to identify root causes and implement reliable solutions.\n\nOptimize model training and inference for memory usage, computational efficiency, throughput, and performance.\n\nDesign and execute tests to verify implementation correctness and compliance with objective performance requirements.\n\nReview and validate challenging machine learning engineering tasks, including existing code and proposed solutions.\n\nUse coding agents as part of the development workflow to accelerate implementation, debugging, testing, and code review while validating generated results.\n\nDocument technical approaches, implementation decisions, test results, and performance findings clearly.\n\nDeliver high-quality, reproducible task submissions within project deadlines.\nRequirements\nMaster's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.\n\nStrong professional or research experience in machine learning and practical ML engineering.\n\nStrong Python programming skills, including the ability to implement, debug, test, and optimize non-trivial code.\n\nHands-on experience using coding agents within a Python development workflow.\n\nUnderstanding of machine learning model development, training and inference workflows, and evaluation methods.\n\nAbility to build reproducible implementations and verify correctness through systematic testing.\n\nStrong quantitative reasoning and problem-solving skills, particularly when diagnosing numerical or computational issues.\n\nAbility to work independently, manage technical tasks, and meet defined quality and submission requirements.\n\nStrong written communication skills and the ability to explain technical findings.\n\nAvailability to contribute approximately 15 hours per week and begin the first task within 24-48 hours after 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