{"id":3409320,"url":"https://alion.io/job/nityo-infotech-senior-ml-engineer","title":"Senior ML Engineer","company":{"id":696181,"name":"Nityo Infotech","domain":"nityo.com","url":"https://alion.io/company/nityo","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Austin, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":129000,"max_usd":249000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1332},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Kubernetes","optional":false},{"name":"NLP","optional":false},{"name":"OCR","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Embeddings","optional":true},{"name":"GCP","optional":true},{"name":"Python","optional":true},{"name":"RAG","optional":true},{"name":"SharePoint","optional":true}],"status":"live","first_seen_at":"2026-10-28T15:55:06Z","employer_posted_date":null,"last_verified_at":"2026-10-28T15:55:06Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"The Opportunity\nCustomer is seeking a hands-on AI/ML contractor to design, build, deploy, and operate enterprise-grade AI/ML and GenAI solutions that improve automation, decisioning, and processing at scale. This role requires building and training fit-for-purpose models in a controlled financial-services environment with limited access to public models and external services, not just configuring third-party tools. The contractor will also mentor existing engineers to strengthen the team's AI/ML capability.\nWhat You'll Do\nOwn end-to-end delivery of production AI/ML solutions, from problem framing and data analysis through modeling, deployment, monitoring, and retraining.\nBuild, train, and validate models (supervised, unsupervised, NLP, retrieval, document intelligence, computer vision, GenAI) using approved data and platforms.\nEstablish rigorous evaluation, explainability, bias assessment, and model governance practices suited to a regulated environment.\nImplement MLOps for versioning, CI/CD, deployment, observability, and drift detection.\nDevelop secure APIs and integration patterns, partnering with architecture, engineering, data, risk, and cybersecurity teams.\nTake prototypes to scalable production and produce clear documentation, runbooks, and knowledge-transfer materials.\nMentor developers through design reviews, pairing, and workshops.\nRequired Qualifications\nBachelor's or advanced degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.\n8+ years in software engineering, data science, or ML, including at least one complete AI/ML lifecycle delivered to production.\nStrong foundation in statistics, probability, linear algebra, optimization, and model evaluation.\nTech stack will be a combo of onprem tooling like dbs, confluence, sharepoint, and Google Cloud Platform services\nHands-on model development in Python with standard ML libraries, plus experience with NLP, embeddings, RAG, LLMs, VLMs, or document intelligence.\nSolid grasp of data preparation, feature engineering, class imbalance, leakage prevention, and tuning.\nExperience with MLOps, containerization, model registries, and secure REST APIs and microservices.\nAbility to work within financial-services constraints around privacy, model risk, explainability, and auditability.\nProven mentoring ability and strong communication with technical and non-technical audiences in Agile, distributed teams.\nPreferred\nCloud-native architecture, Kubernetes, and enterprise CI/CD.\nOCR and Intelligent Document Processing.\nRetrieval and grounding solutions built without relying on pre-packaged frameworks.\nSQL/NoSQL, vector search, and data pipelines.\nFinancial services or other regulated-industry background","description_format":"text","description_chars":2736,"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":["IT Outsourcing & Dedicated Teams","IT Staffing & Staff Augmentation"],"lifecycle":[{"event":"open","at":"2026-10-28T16:53:35Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 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