{"id":67348,"url":"https://alion.io/job/inabia-mlops-engineer-databricksaws-inabia-software-consulting-inc-","title":"MLOps Engineer (Databricks/AWS) - Inabia Software & Consulting Inc.","company":{"id":3098,"name":"Inabia","domain":"inabia.com","url":"https://alion.io/company/inabia","size_band":"201-500","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"JazzHR","truth_index":{"grade":"A","score":100,"open_postings":13,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":9,"computed_at":"2026-10-30T05:48:23Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Columbus, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":132000,"max_usd":262000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":890},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Bitbucket","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-08-20T17:02:12Z","employer_posted_date":"2026-09-26","last_verified_at":"2026-10-30T03:37:37Z","board_verified":true,"closed_at":null,"days_open":70,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":69},"description":"Overview\nInabia is seeking an MLOps Engineer (Databricks/AWS) to design, develop, and maintain end-to-end machine learning operations pipelines on Databricks running on AWS. This role demands deep hands-on expertise with Databricks Machine Learning, MLflow, and a broad suite of AWS services to build scalable, production-grade ML systems. The ideal candidate will partner closely with Data Scientists, Data Engineers, and Platform Engineering teams to productionize models and ensure robust, governed, and cost-efficient deployments.\nLocations: Columbus, OH - Dallas, TX - Atlanta, GA (Onsite only)\nResponsibilities\nDesign, develop, and maintain end-to-end MLOps pipelines on Databricks running on AWS.\nBuild and automate machine learning workflows covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring.\nDeploy and manage ML models using MLflow Model Registry and Databricks Model Serving.\nDevelop and maintain CI/CD pipelines for ML solutions across development, staging, and production environments.\nCollaborate with Data Scientists to productionize machine learning models and ensure reliable, repeatable deployments.\nMonitor model health, prediction quality, data drift, and system performance, and implement automated retraining strategies where required.\nOptimize Databricks workloads for performance, scalability, and cost efficiency.\nImplement Infrastructure as Code using Terraform to provision and manage Databricks and AWS resources.\nEnsure platform security, governance, and compliance using Unity Catalog and AWS IAM.\nTroubleshoot production issues, perform root cause analysis, and continuously improve platform reliability.\nDocument MLOps processes, deployment standards, and operational best practices.\nKey Qualifications\n10+ years of relevant experience in MLOps or a closely related data/ML engineering discipline.\nStrong hands-on experience with Databricks Machine Learning.\nProficiency in Python, PySpark, and SQL for developing and operationalizing machine learning solutions.\nHands-on experience with MLflow for experiment tracking, model registry, model versioning, and lifecycle management.\nExperience deploying and managing machine learning models using Databricks Model Serving and batch inference pipelines.\nStrong understanding of the end-to-end ML lifecycle, including feature engineering, training, validation, deployment, monitoring, and retraining.\nExperience building scalable ML pipelines using Databricks Workflows and Delta Lake.\nHands-on experience with AWS services including S3, IAM, EC2, Lambda, ECR, ECS/EKS, CloudWatch, and Secrets Manager.\nExperience implementing CI/CD pipelines for Databricks and ML workloads using Git, Bitbucket, Jenkins, and Databricks Asset Bundles (DAB).\nExperience with infrastructure automation using Terraform.\nStrong understanding of Apache Spark architecture, optimization, and distributed data processing.\nExperience working with Unity Catalog for governance, security, and access management.\nKnowledge of model monitoring, data drift detection, and automated retraining strategies.\nUnderstanding of MLOps best practices including reproducibility, versioning, testing, and governance.\nExcellent analytical, problem-solving, and communication skills.\nPreferred Qualifications\nExperience with multi-environment Databricks deployments spanning development, staging, and production.\nFamiliarity with cost optimization strategies for large-scale Databricks and AWS workloads.\nPrior experience documenting MLOps operational standards for cross-functional teams.","description_format":"text","description_chars":3578,"description_truncated":false,"requirements":{"experience_years_min":10,"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 Consulting & Digital Transformation","IT Staffing & Staff Augmentation","Analytics & BI Consulting"],"lifecycle":[{"event":"open","at":"2026-08-20T17:02:12Z"},{"event":"close","at":"2026-08-20T22:59:02Z"},{"event":"reopen","at":"2026-08-30T02:35:01Z"}],"visa":[],"liveness":{"score":12,"band":"cold","label":"Long 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