{"id":3163397,"url":"https://alion.io/job/veriday-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":689351,"name":"Veriday","domain":"veriday.com","url":"https://alion.io/company/veriday","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"BambooHR","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cincinnati, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":113000,"max_usd":251000,"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":"Amazon SageMaker","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Db2","optional":false},{"name":"dbt","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Git","optional":false},{"name":"GitHub","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab","optional":false},{"name":"Grafana","optional":false},{"name":"Incident Management","optional":false},{"name":"Java","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenShift","optional":false},{"name":"Pandas","optional":false},{"name":"Prometheus","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false},{"name":"Airflow","optional":true},{"name":"Argo Workflows","optional":true},{"name":"Feast","optional":true},{"name":"GCP","optional":true},{"name":"Kubeflow","optional":true},{"name":"MLFlow","optional":true},{"name":"Recommender Systems","optional":true}],"status":"live","first_seen_at":"2026-10-23T16:42:09Z","employer_posted_date":"2026-10-23","last_verified_at":"2026-10-29T06:48:50Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Veriday Inc. is seeking an experienced Machine Learning Engineerto design, build, and operate scalable machine learning platforms and production ML systems for a 6-month contract assignment with a reputed banking client in Cincinnati, OH. You will own the end-to-end ML lifecycle, from feature engineering and model deployment to monitoring, governance, and continuous retraining. You will also help establish enterprise MLOps capabilities such as a Feature Store, Model Registry, automated CI/CD/CT pipelines, and real-time scoring. You will work closely with data scientists, data engineers, software engineers, and business stakeholders, ideally in a regulated industry such as banking, financial services, healthcare, insurance, or telecom.\nEngagement: Contract assignment with a reputed banking client \nLocation: Cincinnati, OH (hybrid, 3 days per week on-site)\nContract Duration: 6 months, with potential extension \nEmployment Type: W2 only \nResponsibilities\nDesign, build, and optimize scalable, reusable ML platforms and production-grade ML systems that cover model development, training, validation, deployment, and monitoring.\nManage the end-to-end ML lifecycle, including model versioning, experiment tracking, reproducibility, and governance.\nBuild and maintain automated CI/CD/CT pipelines for model testing, validation, deployment, rollback, and retraining, using infrastructure-as-code and automated environment provisioning.\nDesign and support enterprise Feature Stores and a Model Registry to improve feature reuse, consistency, and model governance.\nPartner with data engineering to build scalable training and inference data pipelines that integrate with data warehouses, data lakes, and operational sources, with strong data quality, lineage, and observability.\nDevelop frameworks for batch and real-time inference, including low-latency, event-driven scoring platforms built on streaming technologies.\nImplement model monitoring and alerting for performance, data quality, data/concept/feature drift, and system health, with incident management and retraining strategies.\nOptimize ML systems for performance, reliability, maintainability, and cost efficiency.\nImplement MLOps governance and ensure compliance with security, privacy, risk, and regulatory requirements, including auditability, explainability, and documentation.\nCollaborate with data scientists, product owners, and engineers to translate business needs into technical solutions, and mentor junior engineers while driving MLOps standards and best practices.\nRequired Skills\n5+ years of experience in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering, including 3+ years building and supporting production ML systems.\nDemonstrated experience implementing end-to-end ML lifecycle management: deployment and orchestration, experiment tracking, model versioning, automated retraining, and Responsible AI/model governance.\nHands-on experience operating ML workloads in the cloud (AWS SageMaker, Azure Machine Learning, or Google Vertex AI), supporting both batch and real-time solutions.\nStrong proficiency in Python and SQL; Java, Scala.\nExperience with Feature Store architecture and Model Registry implementation.\nExperience with data platforms and transformation tools such as Snowflake, Databricks, IBM DB2 (or equivalent RDBMS), data lakes, dbt, Spark, PySpark, and Pandas, working with large-scale structured and unstructured data.\nExperience building CI/CD pipelines for ML workloads using Git/GitHub/GitLab and Jenkins, GitHub Actions, Azure DevOps, or equivalent, plus Terraform or other infrastructure-as-code tools.\nExperience with Docker and Kubernetes (OpenShift preferred), plus Linux administration and shell scripting.\nExperience with streaming and event-driven architectures (Apache Kafka) and real-time inference pipelines.\nExperience with monitoring and observability tools such as Prometheus, Grafana, the ELK Stack, or cloud-native monitoring. Experience in regulated industries is highly desirable.\nPreferred Skills\nExperience implementing enterprise Feature Stores and designing Model Registry and ML governance frameworks.\nExperience building real-time decisioning or scoring platforms for use cases such as credit risk, fraud, customer analytics, or recommendation systems.\nFamiliarity with MLflow, Kubeflow, Airflow, Argo Workflows, Feast, SageMaker Pipelines, or similar platforms.\nKnowledge of distributed systems and software architecture patterns.\nFamiliarity with AI/ML regulatory frameworks and model risk management practices.\nRelevant cloud certifications (AWS, Azure, GCP).\nWhat We Offer\nCompetitive hourly rate\nA collaborative and dynamic work environment\nThe opportunity to work on cutting-edge projects with a leading banking client\nIf you have the required skills and are ready for an exciting challenge, we encourage you to apply.","description_format":"text","description_chars":4881,"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":["IT Consulting & Digital Transformation"],"lifecycle":[{"event":"open","at":"2026-10-23T16:42:09Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":5,"expected_fill_days":30,"reasons":["conf:3","velocity","win:early"],"computed_at":"2026-10-29T05:49:05Z"},"pay":null,"html_url":"https://alion.io/job/veriday-machine-learning-engineer","json_url":"https://alion.io/job/veriday-machine-learning-engineer.json","meta":{"generated_at":"2026-10-29T09:44:08Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":14731,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-30T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":689351},"rest":"https://alion.io/mcp/rest/get_company?id=689351"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fveriday-machine-learning-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fveriday-machine-learning-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fveriday-machine-learning-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/veriday-machine-learning-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fveriday-machine-learning-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3163397}},{"tool":"search_jobs","arguments":{"company":"veriday.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3163397},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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