{"id":758977,"url":"https://alion.io/job/permute-senior-research-engineer-ml-systems","title":"Senior Research Engineer - ML Systems","company":{"id":686541,"name":"Permute","domain":"permute.ai","url":"https://alion.io/company/permute","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"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":["Chicago, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Quantization","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Transformers","optional":false},{"name":"Triton","optional":false}],"status":"live","first_seen_at":"2026-08-25T16:58:56Z","employer_posted_date":"2026-08-25","last_verified_at":"2026-09-30T21:11:48Z","board_verified":true,"closed_at":null,"days_open":36,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":36},"description":"Senior Research Engineer - ML Systems\nEmployment Type: Full-time\nCompany: Permute (www.permute.ai)\nOverview\nPermute is seeking a Senior Research Engineer to productionize, optimize, and extend the model systems that power AI reasoning over structured data. This role is for builders who can move from research ideas to reliable production systems, including the profiling, testing, and failure handling that prototypes often skip.\nWe care as much about how you think and build as we do about your background. The ideal candidate can implement research, diagnose model and systems performance, write clean production code, and make sound architectural decisions in a fast-moving startup environment.\nResponsibilities\nProductionize and optimize our existing learned evidence architecture for structured data\n\nImprove training and inference performance, including throughput, latency, memory use, reliability, and cost\n\nPort and optimize model training and inference workloads from CPU to GPU\n\nBuild production systems supporting model training, evaluation, deployment, and inference\n\nDevelop tooling for experimentation, reproducibility, monitoring, and observability\n\nWrite clean, maintainable Python and PyTorch systems that integrate with Permute's broader platform\n\nDesign and evaluate new heads, layers, objectives, and fine-tuning methods\n\nExplore new model variants, including transformer-based architectures and reinforcement learning\n\nCollaborate with engineering and product teams to deliver model capabilities that power production AI features\n\nRequired Qualifications\nStrong background in machine learning research and ML systems\n\nExperience building and training models with PyTorch\n\nStrong foundation in algorithms, statistics, optimization, and experimental design\n\nStrong software engineering and system architecture skills\n\n5+ years building ML or performance-sensitive software systems\n\nPreferred Background\nDegree in Mathematics, Physics, Computer Science, or a related technical field\n\nExperience with:\nEnd-to-end production ML systems\n\nModel training, MLOps, evaluation, and deployment\n\nPerformance engineering, including CUDA, Triton, quantization, or model compilation\n\nTransformers, fine-tuning, post-training, or reinforcement learning\n\nMeaningful contributions to open-source ML frameworks or model implementations","description_format":"text","description_chars":2338,"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":["Artificial Intelligence","Cybersecurity","AI Agents"],"lifecycle":[{"event":"open","at":"2026-09-11T17:56:39Z"}],"liveness":{"score":26,"band":"fade","label":"Fading","p_open":1,"p_active":0.575,"p_room":0.45,"age_days":35,"expected_fill_days":23,"reasons":["conf:4","win:tail"],"computed_at":"2026-09-30T05:45:00Z"},"pay":{"stated_usd_annual":250000,"is_top_pay":true},"html_url":"https://alion.io/job/permute-senior-research-engineer-ml-systems","json_url":"https://alion.io/job/permute-senior-research-engineer-ml-systems.json","meta":{"generated_at":"2026-10-01T02:47:27Z","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":2155,"day_limit":5000,"remaining_today":2845,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}