{"id":577066,"url":"https://alion.io/job/fundamental-studio-ltd-applied-ai-engineer","title":"Applied AI Engineer","company":{"id":308943,"name":"Fundamental Studio Ltd.","domain":"fundamental.bg","url":"https://alion.io/company/fundamental-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"C","score":62,"open_postings":25,"ghost_share":0.64,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-02T06:13:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["DE","FR","GB","AT","BE","BG","HR","CZ","DK","FI","HU","IE","IL","IT","NL","NO","PL","RO","ES","SE","CH","EE","GR","IS","LV","LI","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":32,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"PyBind11","optional":false},{"name":"PyO3","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"Cython","optional":true},{"name":"Embeddings","optional":true},{"name":"PyTorch","optional":true}],"status":"live","first_seen_at":"2026-05-20T08:56:18Z","employer_posted_date":"2026-05-20","last_verified_at":"2026-11-02T20:51:00Z","board_verified":true,"closed_at":null,"days_open":166,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":165},"description":"About Fundamental\nFundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict.\nAt Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.\nKey responsibilities\nTake part in development and optimization of a large neural network-based tabular model implemented in Python\n\nProfile training and inference pipelines to identify performance bottlenecks\n\nRewrite critical components in Rust (via PyO3 or custom extensions) where Python limits us, with C++ (via PyBind11 or custom extensions) as a secondary option where appropriate\n\nImprove memory efficiency, latency, and throughput across model pipelines\n\nEnsure correctness, numerical stability, and reproducibility as the model evolves\n\nCollaborate with ML researchers on productionizing new capabilities\n\nMaintain clean abstractions, comprehensive tests, and clear documentation\n\nShape architectural decisions for our ML systems handling tabular data\n\nMust have\nStrong software engineering fundamentals with expert-level Python and Rust\n\nHands-on experience bridging Python and Rust (PyO3, maturin, or custom extensions)\n\nExperience developing and maintaining ML models in production\n\nStrong understanding of neural networks\n\nTrack record of optimizing performance-critical code\n\nStrong profiling and debugging skills (CPU, memory, latency)\n\nNice to have\nExperience with tabular ML approaches (transformers, tree/NN hybrids, learned embeddings)\n\nWorking proficiency in C++ and experience bridging Python and C++ (PyBind11, Cython, or custom extensions)\n\nFamiliarity with PyTorch internals or writing custom ops (Rust or C++)\n\nExperience optimizing training loops, data pipelines, or inference engines\n\nBackground in numerical computing or systems programming\n\nExposure to large-scale ML infrastructure (distributed training, batching, caching)\n\nExperience with the Rust async ecosystem (tokio) or SIMD/parallelism crates (rayon, ndarray)\n\nBenefits\nCompetitive compensation with salary and equity\n\nComprehensive health coverage for you and your dependents\n\nPaid parental leave for 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