{"id":2291316,"url":"https://alion.io/job/dna325-principal-machine-learning-engineer","title":"Principal Machine Learning Engineer","company":{"id":4411063,"name":"DNA325","domain":"dna325.com","url":"https://alion.io/company/dna325","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["DE","ID","IE","PL","ES","SE","CH","PT"],"hiring_countries_total":8,"salary":null,"salary_estimate":{"min_usd":141000,"max_usd":298000,"period":"year","method":"global_role_seniority_cell","sample_n":1041},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"DeepSpeed","optional":false},{"name":"DPO","optional":false},{"name":"Fine-tuning","optional":false},{"name":"FSDP","optional":false},{"name":"JAX","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"LoRA","optional":false},{"name":"Megatron-LM","optional":false},{"name":"Model Distillation","optional":false},{"name":"PyTorch","optional":false},{"name":"QLoRA","optional":false},{"name":"Quantization","optional":false},{"name":"Ray","optional":false},{"name":"SFT","optional":false},{"name":"Diffusion Models","optional":true},{"name":"LLM","optional":true},{"name":"Multimodal AI","optional":true},{"name":"PEFT","optional":true},{"name":"PPO","optional":true},{"name":"RLHF","optional":true},{"name":"Spark","optional":true},{"name":"TensorRT","optional":true},{"name":"TensorRT-LLM","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-11T18:32:46Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-12T05:11:12Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Our client is an AI-native product company built to replace how billions of people manage their digital lives - starting with email, notes, and task tools that were never designed to be AI-native. It's backed by multi-million-dollar investment and built remote-first from day one, with a clear target: cut the time it takes users to get everyday things done by roughly 90%. That means solving the problems most AI products avoid - long-running workflows, persistent context, and reliable behavior under real-world, non-deterministic conditions. The team is small and high-talent-density by design, not by necessity, and moves at a pace that matches the scale of what it's building.\nAbout the Role\nYou'll be responsible for turning research direction into working, production-grade ML systems. This role owns the execution layer of the company's intelligence - training pipelines, inference systems, evaluation tooling, and deployment.\nWhat You'll Work On\nBuild and own end-to-end ML pipelines spanning data, training, evaluation, inference, and deployment\nFine-tune and adapt models using state-of-the-art methods - LoRA, QLoRA, SFT, DPO, distillation\nArchitect and operate scalable inference systems, balancing latency, cost, and reliability\nDesign and maintain data systems for high-quality synthetic and real-world training data\nImplement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership\nOwn production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies\nCollaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products\nMake pragmatic trade-offs and ship improvements quickly, learning from real usage\nWork under real production constraints: latency, cost, reliability, and safety\nRequirements\nStrong background in deep learning and transformer-based architectures\nHands-on experience training, fine-tuning, or deploying large-scale ML models in production\nProficiency with at least one modern ML framework (PyTorch, JAX), and ability to pick up others quickly\nExperience with distributed training and inference frameworks (DeepSpeed, FSDP, Megatron, ZeRO, Ray)\nStrong software engineering fundamentals - you write robust, maintainable, production-grade systems\nExperience with GPU optimization, including memory efficiency, quantization, and mixed precision\nComfort owning ambiguous, zero-to-one ML systems end-to-end\nA bias toward shipping, learning fast, and improving systems through iteration\nLocation\nRemote, open to candidates in Poland, Portugal, Spain, Sweden, Switzerland, Germany, Ireland, Indonesia, Seoul, or Singapore.\nNice to Have\nExperience with LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer\nContributions to open-source ML or systems libraries\nBackground in scientific computing, compilers, or GPU kernels\nExperience with RLHF pipelines (PPO, DPO, ORPO)\nExperience training or deploying multimodal or diffusion models\nExperience with large-scale data processing (Apache Arrow, Spark, Ray)\nWhat to Expect\nThe best products in the world are built by small, world-class teams. Decisions are made collectively, at rapid speed - balancing high-quality shipping with fast learning. You'll be expected to bring structure, exercise judgment, and execute independently.\nCompensation and benefits are competitive and vary by location; the package includes base salary and equity, discussed openly with you as part of the process.\nIf there's a fit, expect 3-4 interviews total, followed by a prompt, transparent decision. To be considered, please make sure to answer the screening questions in the application form - we're not able to review submissions that skip them.","description_format":"text","description_chars":3776,"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":["Equity"],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"country"},{"name":"Indonesia","iso":"ID","kind":"country"},{"name":"Ireland","iso":"IE","kind":"country"},{"name":"Poland","iso":"PL","kind":"country"},{"name":"Spain","iso":"ES","kind":"country"},{"name":"Sweden","iso":"SE","kind":"country"},{"name":"Switzerland","iso":"CH","kind":"country"},{"name":"Portugal","iso":"PT","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-10-11T18:32:46Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":35,"reasons":["conf:1","win:early"],"computed_at":"2026-10-12T06:55:09Z"},"pay":null,"html_url":"https://alion.io/job/dna325-principal-machine-learning-engineer","json_url":"https://alion.io/job/dna325-principal-machine-learning-engineer.json","meta":{"generated_at":"2026-10-12T08:54:30Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":13382,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-13T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":4411063},"rest":"https://alion.io/mcp/rest/get_company?id=4411063"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fdna325-principal-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fdna325-principal-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fdna325-principal-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/dna325-principal-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fdna325-principal-machine-learning-engineer"}]}