{"id":3297799,"url":"https://alion.io/job/makpar-ml-engineer","title":"ML Engineer","company":{"id":679366,"name":"Makpar","domain":"makpar.com","url":"https://alion.io/company/makpar","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":126000,"max_usd":281000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Machine Learning","optional":false},{"name":"NumPy","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Confluence","optional":true},{"name":"Jira","optional":true}],"status":"live","first_seen_at":"2026-10-26T18:49:47Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-29T07:36:20Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Makpar has an exciting opportunity for an ML Engineer to join our growing team. The ML Engineer is responsible for developing, implementing, and optimizing machine learning models and data-driven solutions. Works closely with data engineers, developers, and stakeholders to prepare data, train and evaluate models, integrate ML capabilities, and support model deployment, monitoring, and continuous improvement.\nRole Specific Duties/ Role Responsibilities:\nSolve highly complex technical problems using Appian and supporting platforms\nMentor junior developers and conduct peer code reviews\nDesign and develop business logic, process models/flows, and UI screens in a BPM-based system\nProvide technical leadership to Agile development teams\nDesign architectural frameworks using industry-standard methodologies\nResolve systems integration issues and present technical material to senior client leadership\nMachine Learning Development & Optimization\nDevelop, train, test, and optimize machine learning models to support predictive analytics, classification, and data-driven decision-making.\nEvaluate model performance, accuracy, and reliability to identify opportunities for improvement.\nSupport the development and enhancement of scalable, reusable ML capabilities.\nData Engineering & Feature Development\nSupport data ingestion, preprocessing, normalization, validation, and feature engineering across multiple data sources.\nDevelop data enrichment capabilities to improve model performance and analytical insights.\nAssist in building reusable data pipelines and preparing datasets for model training, evaluation, and inference.\nML Integration & CI/CD Support\nIntegrate ML models with data pipelines, APIs, and application services to support operational use cases.\nSupport model packaging, version control, deployment automation, and CI/CD pipeline improvements.\nAssist with deployment, troubleshooting, and production readiness activities across development, test, and production environments.\nTesting, Validation & Performance Monitoring\nDevelop and execute model testing and validation procedures to assess accuracy, reliability, and performance.\nMonitor model outputs and identify data quality issues, defects, and opportunities for optimization.\nSupport ongoing model evaluation, maintenance, and continuous improvement.\nAgile Team Collaboration\nCollaborate with data engineers, software developers, architects, and product stakeholders to align ML solutions with business and technical requirements.\nTranslate business needs into ML experiments, technical designs, and implementation tasks.\nContribute to technical planning, solution design, and delivery of new ML capabilities.\nDocumentation & Knowledge Management\nDocument model architecture, experiments, evaluation results, deployment procedures, and technical decisions.\nMaintain technical documentation and implementation guidance to support knowledge transfer and maintainability.\nShare findings, best practices, and lessons learned to improve team effectiveness and consistency.\nRequired Qualifications:\nBachelor’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related technical field.\nEquivalent combinations of relevant education, technical training, and professional experience may be considered.\nExperience developing, training, evaluating, and optimizing machine learning models using Python and common ML libraries such as scikit-learn (sklearn), pandas, and NumPy.\nHands-on experience with Databricks for data processing, model development, experimentation, and ML workflows.\nExperience with data preprocessing, feature engineering, data validation, and working with structured and semi-structured datasets.\nFamiliarity with ML model deployment, REST APIs, and integration with data pipelines or application services.\nExperience with Git and GitHub for source control, collaboration, and code management.\nExperience developing or maintaining CI/CD workflows using GitHub Actions, including automated testing, build processes, and deployment pipelines.\nUnderstanding of ML model evaluation metrics, testing methodologies, and model performance monitoring.\nExperience writing clean, maintainable, and well-documented Python code.\nStrong analytical, problem-solving, troubleshooting, and communication skills.\nAbility to collaborate effectively with cross-functional teams, including ML engineers, data engineers, software developers, and product stakeholders.\nAbility to work collaboratively in an Agile team environment.\nPreferred Qualifications\nRelevant certifications or specialized training in machine learning, Databricks, cloud technologies, or MLOps.\nExperience in government contracting, regulated industries, or large enterprises\nFamiliarity with identity, access management, data platforms, or enterprise SaaS ecosystems\nExperience working with Jira and Confluence\nAdditional Requirements as per contract/client (Optional or Preferred):\n Candidates must be a US Citizen or a Legal Permanent Resident (Green Card status) for 3 years and be Federal Tax compliant.","description_format":"text","description_chars":5122,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":true,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","Management Consulting"],"lifecycle":[{"event":"open","at":"2026-10-26T22:23:39Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring 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