{"id":1605149,"url":"https://alion.io/job/intuit-senior-machine-learning-engineer-foundational-models-and-agentic-systems","title":"Senior Machine Learning Engineer, Foundational Models and Agentic systems","company":{"id":16628,"name":"Intuit","domain":"intuit.com","url":"https://alion.io/company/intuit","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Radancy","truth_index":{"grade":"B","score":75,"open_postings":81,"ghost_share":0,"stale_share":0.988,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-10-12T06:55:09Z"}},"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":["Tel Aviv, Israel"],"countries":["IL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":138000,"max_usd":350000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1986},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Docker","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"Quantization","optional":false},{"name":"Spark","optional":false},{"name":"vLLM","optional":false}],"status":"live","first_seen_at":"2026-08-17T00:00:00Z","employer_posted_date":"2026-08-17","last_verified_at":"2026-10-12T05:42:41Z","board_verified":true,"closed_at":null,"days_open":56,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":56},"description":"Join the innovative Generative AI group, to help build the next generation of awesome products and experiences using cutting-edge technology.\nIf you love having stretch goals, challenges, and making customers incredibly happy while fostering your obsessive need for elegant, state of the art technology which drives impact and creates awesome user experiences, this is the job for you.\nYou will collaborate with many teams in Intuit and contribute to many components in different business units. We love engineers who lead the change, communicate with customers, and deliver the most beautiful and intuitive applications.\nIn this role, you’ll:\nBe part of a vibrant team of Data Scientists and ML Engineers\n\nBe expected to help code, optimize, and deploy GenAI models at scale, using the latest industry tools and techniques\n\nHelp automate, deliver, monitor, and improve GenAI solutions\n\nResponsibilities\nDesign and build systems, which improve Generative AI inference, quantization, optimization, finetuning, and evaluation\n\nWork cross-functionally with product managers, data scientists, and engineers to understand, implement, refine, and design Generative AI models\n\nEffectively communicate results to peers and leaders\n\nExplore the state-of-the-art technologies and apply them to deliver customer benefits.\n\nInteract with a variety of data sources, working closely with peers and partners to refine features from the underlying data and build end-to-end pipelines\n\nQualifications\nLLM experience: LangChain, vLLM, HuggingFace toolkit\n\nMachine Learning oriented languages, tools, and frameworks: Spark, Python\n\nCloud technologies, in particular AWS, and Software container technology: Docker, Kubernetes, KubeFlow / MLflow\n\nExperience with designing and developing Generative AI architectures\n\nMachine learning techniques (classification, regression, and clustering) and principles (training, validation, and testing)\n\nData query and data processing tools or systems: relational, NoSQL, stream processing\n\nDistributed computing systems and related technologies: Spark, Hive\n\nSoftware engineering fundamentals: version control systems (Git, Github) and workflows, and ability to write production-ready code\n\nComputer science fundamentals: data structures, algorithms, performance, complexity, and implications of computer architecture on software performance (I/O and memory tuning)\n\nMathematics fundamentals: linear algebra, calculus, probability\n\nBS, MS, or PhD degree in Computer Science or related field, or equivalent practical\n\nIntuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. 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