{"id":2521359,"url":"https://alion.io/job/albiware-senior-machine-learning-engineer-llms","title":"Senior Machine Learning Engineer (LLMs)","company":{"id":3778546,"name":"Albiware","domain":"albiware.com","url":"https://alion.io/company/albiware-inc","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","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":null,"salary_estimate":{"min_usd":136000,"max_usd":259000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1124},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Claude Code","optional":false},{"name":"Fine-tuning","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"LoRA","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RLHF","optional":false},{"name":"SFT","optional":false},{"name":"DeepSpeed","optional":true},{"name":"FSDP","optional":true},{"name":"Megatron-LM","optional":true},{"name":"NLP","optional":true},{"name":"PEFT","optional":true},{"name":"Quantization","optional":true},{"name":"Speculative Decoding","optional":true},{"name":"Triton","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-03-09T00:00:00Z","employer_posted_date":"2026-03-09","last_verified_at":"2026-10-14T18:21:11Z","board_verified":true,"closed_at":null,"days_open":219,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":219},"description":"We’re building deeply integrated LLMs into a real product used daily by restoration companies running thousands of jobs. This is not a “prompt engineer” role. You’ll design, train, and ship domain-specific language models that automate real workflows and move real revenue.\nYou will:\nOwn end-to-end LLM systems: architecture, training, evals, and iteration\nFine-tune and extend existing models (LoRA, instruction tuning, RLHF)\nBuild and maintain data pipelines from product databases, documents, APIs, and logs\nShip reliable, monitored, production models with clear guardrails\nCollaborate closely with product and engineering to turn messy real-world problems into working systems\nBuild and coordinate the AI engineering team\nUse Claude Code as a core tool for development, refactors, tests, and experiments\nThis is for you if:\n“How does this actually work under the hood?” is your default question\nYou’re fine sitting with a hard problem for days and reading papers on weekends to figure it out\nIf there’s something interesting to learn or solve, it doesn’t matter if it’s Saturday or 1 a.m., you’re in\nYou build side projects nobody asked for and write cleaner code than anyone requires\nYou’re quietly competitive, self-taught in at least one major skill, and think in systems\nYou’re slightly allergic to meetings without a clear purpose or owner\nRequirements\n5+ years of real world experience in ML / AI engineering\nProven experience training or substantially contributing to training LLMs (not just calling APIs)\nDeep understanding of transformers, attention, and training dynamics\nStrong Python plus PyTorch or JAX\nExperience with large-scale data pipelines and experiment tracking\nHands-on fine-tuning (LoRA, instruction / SFT, RLHF or similar)\nComfortable using Claude Code as part of your daily workflow\nAble to explain complex systems simply to non-technical stakeholders and go deep with experts\nTrack record of owning projects end-to-end and mentoring other engineers\nNice to have:\nDistributed training (FSDP, DeepSpeed, Megatron, etc.)\nInference optimization (quantization, speculative decoding, vLLM, Triton)\nExperience shipping LLM features in production SaaS\nOpen-source contributions or published work or patents in ML / NLP\nMicrosoft Foundry experience \nBenefits\nCompetitive salary (based on experience and location)\nGenerous PTO\nMedical, dental, and vision coverage\n401(k) plan\nHigh ownership and autonomy over your work\nDirect collaboration with a small team of smart, kind, motivated engineers\nAn environment that values deep work, clear thinking, and real impact\nRegular team events and off-sites\nEquipment and learning budget to help you do your best work and keep up with the 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