{"id":3202171,"url":"https://alion.io/job/recruitment-room-machine-learning-researcher-msc-or-phd-remote","title":"Machine Learning Researcher (MSc. or PhD) - Remote","company":{"id":100174,"name":"Recruitment Room","domain":"recruitmentroom.net","url":"https://alion.io/company/recruitment-room","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":null,"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":"inferred_payroll_markers","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AS","WS"],"hiring_countries_total":2,"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":"2026-10-24T07:50:00Z","employer_posted_date":null,"last_verified_at":"2026-10-24T07:50:00Z","board_verified":false,"closed_at":null,"days_open":12,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":12},"description":"Machine Learning Researcher (MSc. or PhD) - Remote\nRole Overview\nEmployment Type: Contract\n\nLocation: Fully Remote, Global\n\nWorkload: Approximately 15 hours per week\n\nCompensation: $60-$120 per hour\n\nPayment Structure: Output-based, with payment for tasks meeting project specifications\n\nAbout the Role\nWe are seeking highly skilled Machine Learning Researchers to contribute to AI training projects involving model development, training and inference systems, numerical computing, performance optimization, and Python engineering.\nThis is a coding-intensive role focused on developing, solving, reviewing, and validating challenging machine learning tasks. You may implement or modify models, build reproducible training and inference workflows, optimize memory usage and computational throughput, and debug numerical or system-level failures.\nYou will apply advanced machine learning knowledge and practical programming skills to ensure implementations meet defined correctness and performance requirements.\nKey Responsibilities\nDevelop and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.\n\nImplement model components, data pipelines, evaluation systems, and numerical methods.\n\nBuild reproducible workflows using Python and command-line tools.\n\nDebug numerical and system-level failures in machine learning implementations.\n\nOptimize memory usage, computational throughput, and model performance.\n\nCreate, solve, review, and validate technical tasks against objective specifications.\n\nUse coding agents as part of your Python development workflow.\n\nRequired Qualifications\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.\n\nPractical proficiency in Python and coding agents.\n\nAbility to implement, debug, and evaluate complex machine learning solutions.\n\nStrong analytical skills and attention to technical correctness.\n\nPreferred Qualifications\nExperience at an established technology company, AI laboratory, research organization, or comparable engineering environment.\n\nSignificant academic research or open-source contributions demonstrating relevant technical depth.\n\nExperience with model training and inference, numerical computing, performance optimization, or reproducible machine learning workflows.\n\nCompensation and Work Arrangement\nThe role offers $60-$120 per hour, with compensation determined by completed tasks that meet project specifications. Task duration may vary depending on experience and workflow, and minimum submission requirements apply.\nThe expected workload is approximately 15 hours per week, with flexible scheduling, including weekends if preferred.\nSelection Process\nSubmit an application and complete the screening questions.\n\nComplete an AI interview of approximately 30 minutes.\n\nParticipate in a hiring manager review.\n\nStart Timeline\nCandidates should be ready to begin promptly. 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