{"id":1253790,"url":"https://alion.io/job/lexisnexis-senior-machine-learning-engineer-i","title":"Senior Machine Learning Engineer I","company":{"id":6793,"name":"LexisNexis","domain":"lexisnexis.com","url":"https://alion.io/company/lexisnexis-legal","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":79,"open_postings":52,"ghost_share":0,"stale_share":0.827,"repost_share":0,"time_to_fill_p50_days":37,"computed_at":"2026-09-29T05:45:00Z"}},"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":["Raleigh, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":104900,"max":174700,"currency":"USD","period":"year","gross":null,"usd_annual":174700},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon Neptune","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Dgraph","optional":false},{"name":"Docker","optional":false},{"name":"ElasticSearch","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Neo4j","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"Ray Serve","optional":false},{"name":"Redis","optional":false},{"name":"TorchServe","optional":false},{"name":"Triton","optional":false},{"name":"Weaviate","optional":false},{"name":"Weights & Biases","optional":false},{"name":"Ray","optional":true}],"status":"closed","first_seen_at":"2026-09-25T18:43:06Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-26T05:37:52Z","board_verified":false,"closed_at":"2026-09-26T05:37:52Z","days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"The Machine Learning Engineer develops, deploys, and maintains scalable AI/ML solutions that meet production standards. They turn data science prototypes into reliable, production-ready services, automate MLOps workflows, and build tools and infrastructure for model training and inference. This role requires strong software engineering, DevOps, and cloud skills, as well as experience with NLP, search technologies, vector and graph databases, and modern MLOps platforms.\nKey responsibilities\nTransform data science experiments into scalable production-ready AI services\nEnable both offline model training and real-time inference through robust model serving pipelines.\nAutomate end-to-end MLOps workflows and develop internal ML tools.\nMonitor production data quality, model versions, cloud costs, and security compliance.\nSupport and maintain infrastructure that empowers the data science team.\nTechnical skills\nProficient in general software engineering principles and practices.\nSkilled in DevOps and cloud-based engineering environments.\nExperience with NLP, search technologies, and modern ML toolkits.\nFamiliar with search engines, vector databases, and graph databases.\nHands-on experience with MLOps platforms and automation tools.\nHands-on experience with Retrieval-Augmented Generation (RAG) and AI agentic solutions, with a strong focus on engineering and productionization.\nCommon tools and technologies\nDocker, Kubernetes, Python, Flask/\nFastAPI, Redis, Solr/ElasticSearch, Weaviate/Qdrant, Neo4j/AWS Neptune/DGraph, AWS/Azure/GCP, MLFlow/KubeFlow/Weights & Biases, TorchServe/Ray Serve/Triton/AWS SageMaker\n\nU.S. National Base Pay Range: $104,900 - $174,700. Geographic differentials may apply in some locations to better reflect local market rates.\n\nThis job is eligible for an annual incentive bonus.\n\nWe know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Clickhereto access benefits specific to your location.\nWe are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.\nCriminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scamshere.\nPlease read our Candidate Privacy Policy.\nWe are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.\nUSA Job Seekers:\nEEO Know Your Rights.","description_format":"text","description_chars":2896,"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":["Cybersecurity","Legal AI","Legal Software"],"lifecycle":[{"event":"open","at":"2026-09-25T18:43:06Z"},{"event":"close","at":"2026-09-26T05:37:52Z"}],"liveness":null,"pay":{"stated_usd_annual":174700,"is_top_pay":false},"html_url":"https://alion.io/job/lexisnexis-senior-machine-learning-engineer-i","json_url":"https://alion.io/job/lexisnexis-senior-machine-learning-engineer-i.json","meta":{"generated_at":"2026-09-30T05:20:49Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":3714,"day_limit":5000,"remaining_today":1286,"minute_limit":60,"resets_at":"2026-10-01T00:00:00Z"}}}