{"id":4052038,"url":"https://alion.io/job/techstra-solutions-machine-learning-engineer-senior-techstra-solutions","title":"Machine Learning Engineer Senior - Techstra Solutions","company":{"id":4431605,"name":"Techstra Solutions","domain":"techstrasolutions.com","url":"https://alion.io/company/techstra-solutions","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Dallas, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Pinecone","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Weaviate","optional":false},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-11-11T02:14:03Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T02:14:03Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Role Description:\nLeads in the development of cross-functional, multi-platform machine learning software systems. Uses technical knowledge and industry experience to design, build and maintain technology solutions. Utilizes knowledge of advanced probability and statistics to create intricate machine learning algorithms. Applies complex higher level math concepts to build new models and validate existing models. Possesses Machine Learning industry expertise and stays current on best practices, hot topics, and emerging trends. Utilizes industry expertise to inform decisions and recommendations. Performs complex application programming activities including, coding, testing, debugging, documenting, maintaining, and modifying machine learning systems. Works with Data Scientist to understand prototype, and suggests modifications as necessary. Easily understands the bigger picture and possesses an enterprise-wide view. Skills: Machine Learning Customer Solutions Risk Assessments Technical Knowledge Competitive Advantages Design Enterprise Architecture Framework Experience: 5-7 years related experience.\nExperience implementing production solutions that leverage generative AI and LLMs, agentic frameworks\nImplementation/use of SDLC harnesses for increasing personal and team productivity\nInternal client consultation to elicit and collect requirements, and communicate and align the technical team toward delivery\nModel solution design, build, orchestration and implementation\nExperience building solutions with model governance, risk management, and regulatory adherence at top of mind\nContinuous support of models deployed to production applications\nRelease planning, coordination, and hands on support throughout release windows\nMachine Learning / GenAI\nPython, scikit-learn, PyTorch and/or TensorFlow\nGenerative AI and Large Language Models (LLMs)\nRetrieval-Augmented Generation (RAG), embeddings, vector search\nAgentic AI frameworks such as LangChain, LangGraph, Semantic Kernel, or similar\nModel evaluation, validation, prompt engineering, and model monitoring\nAdvanced probability, statistics, linear algebra, and optimization\nAI/ML Platforms\nAzure Machine Learning, Azure AI Foundry, AWS SageMaker, or equivalent enterprise ML platforms\nAzure OpenAI/OpenAI APIs or comparable foundation-model platforms\nMLflow or similar experiment tracking/model lifecycle tooling\nVector databases/search platforms such as Azure AI Search, Pinecone, Weaviate, or pgvector\nDevelopment & Engineering\nGit/GitHub or Azure DevOps\nREST APIs and microservices\nDocker and containerized deployments\nCI/CD pipelines and automated testing\nJira/Confluence or similar Agile delivery tools\nSDLC practices, source control, code reviews, release management, and production support\nData\nSQL\nData pipelines and data preparation\nStructured and unstructured data\nFeature engineering\nData quality and validation\nAPI and enterprise data integration\nGovernance / Risk Knowledge\nModel governance and model risk management\nResponsible AI concepts\nExplainability, validation, bias/fairness, data privacy, and security\nAuditability and documentation\nRegulatory adherence and production controls","description_format":"text","description_chars":3169,"description_truncated":false,"requirements":{"experience_years_min":5,"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":[],"lifecycle":[{"event":"open","at":"2026-11-11T02:14:03Z"}],"visa":[{"country":"US","licensed_sponsor":true,"adverts_offering_sponsorship_24m":0,"sanctioned_now":false,"evidence":"H-1B filings in 12 months: 8 · green card filings: 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