{"id":2909674,"url":"https://alion.io/job/koantek-senior-ai-engineer","title":"Senior AI Engineer","company":{"id":3800091,"name":"Koantek","domain":"koantek.com","url":"https://alion.io/company/koantek","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":{"grade":"C","score":65,"open_postings":29,"ghost_share":0.586,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-22T06:10:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":135000,"max_usd":248000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":338},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"RAG","optional":false},{"name":"Spark","optional":false},{"name":"Databricks","optional":true}],"status":"live","first_seen_at":"2025-11-07T00:00:00Z","employer_posted_date":"2025-11-07","last_verified_at":"2026-10-23T03:45:13Z","board_verified":true,"closed_at":null,"days_open":350,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":349},"description":"Sr AI Engineer / Data Scientist / MLOps Consultant\nLocation: United States - Remote\nEmployment Type: Full-Time and Contract\nWe\nare seeking an experienced and highly technical Data Scientist to join our\ncustomer-facing consulting team. This remote role requires a blend of advanced\nMachine Learning (ML) expertise, deep knowledge of MLOps principles, and a\nproven track record in client-facing implementation. The successful candidate\nwill be instrumental in designing, deploying, and maintaining production-grade\nML solutions, including advanced Generative AI and Natural Language Processing\n(NLP) models, for our diverse client base.Key Responsibilities\nServe as a primary technical\nconsultant, leading and executing end-to-end ML project implementations\ndirectly with clients, translating complex business problems into robust\ntechnical solutions.\nExhibit excellent communication, presentation, and\nstakeholder management skills to clearly articulate technical findings, proposals, and\nproject status to both technical and non-technical audiences.\nDesign, build, and maintain\nproduction-grade ML pipelines, focusing on continuous integration, continuous\ndelivery (CI/CD), and advanced MLOps practices to ensure reliability and\nscalability of models.\nImplement and optimize\ncutting-edge Generative AI and NLP applications, demonstrating hands-on\nexperience with technologies like Retrieval Augmented Generation (RAG) and\nLarge Language Models (LLMs) in a production setting.\nManage underlying solution\ninfrastructure, demonstrating proficiency in technologies such as Docker,\npipeline orchestrators, and database systems.\nLeverage expertise in\ndistributed computing frameworks, specifically in scalable machine learning and\nhigh-performance data processing (e.g., using technologies like Apache Spark).\nContribute to the strategic\ngrowth of the ML Practice Team, including participation in technical\nassignments and knowledge transfer activities.\nEnsure all client engagements\nand training activities are properly documented and reported via designated\npartner platforms.\nRequired Qualifications\n4+ years of hands-on professional experience developing, deploying,\nand managing Machine Learning models, with a mandatory requirement for productionizing and maintaining models\nin a live environment.\n3+ years of experience in a customer-facing consulting or solutions\narchitect role, focused on technical implementation and delivery.\nExcellent verbal and written communication skills for effective client and\ninternal team interaction.\nExpertise in MLOps lifecycle\nmanagement, including model versioning, testing, monitoring, and automated\ndeployment best practices.\nDemonstrable experience with\ninfrastructure management, encompassing containerization (Docker) and data\npipeline orchestration.\nDeep understanding of\nprogramming for data-intensive and scalable ML applications.\nProven experience in\ndeploying and managing Generative AI and NLP solutions for client applications.\nPreferred Qualifications\nHands-on experience with\nmodern ML platform stacks, such as Databricks MLOps Stacks.\nKnowledge of specific tools\nand techniques used in scalable machine learning and large-scale data\nprocessing.\nDemonstrated commitment to\ncontinuous learning in emerging ML fields, such as LLMs and GenAI application\narchitectures.\nRequirements\nHands-on experience with\nmodern ML platform stacks, such as Databricks MLOps Stacks.\nKnowledge of specific tools\nand techniques used in scalable machine learning and large-scale data\nprocessing.\nDemonstrated commitment to\ncontinuous learning in emerging ML fields, such as LLMs and GenAI application\narchitectures.","description_format":"text","description_chars":3644,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous learning"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Analytics & BI Consulting","Data Engineering & Migration Services"],"lifecycle":[{"event":"open","at":"2026-10-20T09:18:28Z"}],"visa":[],"liveness":{"score":3,"band":"cold","label":"Long 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